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4632
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Discord to Fluxer by @true_lock | Stardance
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true_lock
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0
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4.0
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0
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[]
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[{"post_id": 11963, "ts": "202 [{"post_id": 11963, "ts": "2026-06-19T15:00:20Z", "hours": 1.0, "text": "I cleaned up and restructured the code into multiple files. This should make the program a whole lot easier to maintain : )"}, {"post_id": 12537, "ts": "2026-06-20T14:11:46Z", "hours": 2.0, "text": "Added Emoji Migration. You can now migrate all your custom server emojis to your new fluxer server : )"}, {"post_id": 12707, "ts": "2026-06-20T19:06:05Z", "hours": 1.0, "text": "Working on Role migration right now"}, {"post_id": 13044, "ts": "2026-06-21T10:20:51Z", "hours": 0.0, "text": "Added a popup if specific permissions are missing, instead of just logging a 403/401 error"}]...
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Title: Discord to Fluxer by @true_lock | Stardance Title: Discord to Fluxer by @true_lock | Stardance
Devlogs:
I cleaned up and restructured the code into multiple files. This should make the program a whole lot easier to maintain : )
Added Emoji Migration. You can now migrate all your custom server emojis to your new fluxer server : )
Working on Role migration right now
Added a popup if specific permissions are missing, instead of just logging a 403/401 error...
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1792925641.7571332
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1793789641.7571332
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4633
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SpaceShield by @wigothehacker | Stardance
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wigothehacker
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1
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6.0
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0
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[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-07-02T22:36:47Z", "hours": 6.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "I made a shield for our earth where we analyze the space detect threats and notify our users and show them the potential future threats, the challenging thing is that in order to host it i had to remove advanced features from backend like kafka so that i can host it freely. And what I am proud of is the 3d earth model which help to visualize threats.", "repo": "https://github.com/goal651/spaceShield", "demo": "https://space-shield-six.vercel.app"}]...
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[{"post_id": 21126, "ts": "202 [{"post_id": 21126, "ts": "2026-07-02T22:36:29Z", "hours": 0.3433, "text": "Today I tried to improve ui to match with the current system"}, {"post_id": 6239, "ts": "2026-06-10T14:19:21Z", "hours": 0.3278, "text": "Today I added 3d world map for easy exploring solar flares and fireballs"}, {"post_id": 4131, "ts": "2026-06-07T10:23:04Z", "hours": 0.8844, "text": "Devlog #2: Bypassing Cloud Memory Walls & Fixing CI/CD Pipelines What changed: Optimized the Spring Boot architecture to fit under 512MB RAM constraints, successfully deployed the backend to production, and automated the GitHub Actions Docker build pipeline. The Hurdles & Fixes: Memory Limits: The application ran out of memory on startup. Fix: Added JVM arguments (-Xmx384m -XX:+UseSerialGC) and staggered the NASA API scheduler loops to reduce runtime spikes. Syntax Crash: Spring crashed due to mixing cron and initialDelay in the same scheduler annotation. Fix: Converted the task to a clean fixedRate setup. NASA Null Bug: The app hit a NullPointerException because NASA omits the \"data\" JSON key when zero meteors occur in a week. Fix: Added a defensive null-check function. CI/CD Naming Rule: GitHub Actions failed because Docker tags strictly forbid uppercase letters. Fix: Added a dynamic shell function (tr '[:upper:]' '[:lower:]') into the YAML workflow to automatically force repository paths to lowercase on every git push. Next steps: Connect the newly published Docker package to live web hosting and finish mapping the UI dashboard layout."}, {"post_id": 3756, "ts": "2026-06-06T20:06:59Z", "hours": 4.7572, "text": "Progress update on SpaceShield Global Completed major backend and frontend foundation work: NASA API integration layer Spring Boot controllers, services, repositories, and mappers Kafka producers, consumers, and event models Risk classification engine Scheduled data ingestion Database entities and DTOs Initial Next.js frontend setup Fireball map component Current architecture: NASA APIs → Spring Boot → Kafka → Risk Engine → PostgreSQL → Next.js Dashboard Next steps: Test live NASA data ingestion Complete dashboard UI Connect risk assessments to frontend views Add visualizations for asteroids, solar flares, and fireballs SpaceShield Global is a real-time platform for monitoring and analyzing near-Earth space events using NASA data."}]...
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Title: SpaceShield by @wigothehacker | Stardance
Title: SpaceShield by @wigothehacker | Stardance
Devlogs:
Progress update on SpaceShield Global Completed major backend and frontend foundation work: NASA API integration layer Spring Boot controllers, services, repositories, and mappers Kafka producers, consumers, and event models Risk classification engine Scheduled data ingestion Database entities and DTOs Initial Next.js frontend setup Fireball map component Current architecture: NASA APIs → Spring Boot → Kafka → Risk Engine → PostgreSQL → Next.js Dashboard Next steps: Test live NASA data ingestion Complete dashboard UI Connect risk assessments to frontend views Add visualizations for asteroids, solar flares, and fireballs SpaceShield Global is a real-time platform for monitoring and analyzing near-Earth space events using NASA data.
Devlog #2: Bypassing Cloud Memory Walls & Fixing CI/CD Pipelines What changed: Optimized the Spring Boot architecture to fit under 512MB RAM constraints, successfully deployed the backend to production, and automated the GitHub Actions Docker build pipeline. The Hurdles & Fixes: Memory Limits: The application ran out of memory on startup. Fix: Added JVM arguments (-Xmx384m -XX:+UseSerialGC) and staggered the NASA API scheduler loops to reduce runtime spikes. Syntax Crash: Spring crashed due to mixing cron and initialDelay in the same scheduler annotation. Fix: Converted the task to a clean fixedRate setup. NASA Null Bug: The app hit a NullPointerException because NASA omits the "data" JSON key when zero meteors occur in a week. Fix: Added a defensive null-check function. CI/CD Naming Rule: GitHub Actions failed because Docker tags strictly forbid uppercase letters. Fix: Added a dynamic shell function (tr '[:upper:]' '[:lower:]') into the YAML workflow to automatically force repository paths to lowercase on every git push. Next steps: Connect the newly published Docker package to live web hosting and finish mapping the UI dashboard layout.
Today I added 3d world map for easy exploring solar flares and fireballs
Today I tried to improve ui to match with the current system
Ships:
I made a shield for our earth where we analyze the space detect threats and notify our users and show them the potential future threats, the challenging thing is that in order to host it i had to remove advanced features from backend like kafka so that i can host it freely. And what I am proud of is the 3d earth model which help to visualize threats....
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1793479773.066881
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1793566173.066881
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4634
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My first slack bot! by @aniketh8975 | Stardance
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aniketh8975
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Title: My first slack bot! by @aniketh8975 | Stard Title: My first slack bot! by @aniketh8975 | Stardance...
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1793292999.2461936
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1793897799.2461936
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4635
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Stacksentinel by @Sukuna | Stardance
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Sukuna
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Title: Stacksentinel by @Sukuna | Stardance
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1793285355.245592
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4636
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MAKRYAM by @PanAnton11 | Stardance
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PanAnton11
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Title: MAKRYAM by @PanAnton11 | Stardance
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1793202675.0705485
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4637
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My first slack bot! by @arsyad | Stardance
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arsyad
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Title: My first slack bot! by @arsyad | Stardance
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1793181193.9509428
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1793785993.9509428
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4638
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Untitled by @tanmay | Stardance
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Title: Untitled by @tanmay | Stardance
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4639
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My awesome macropad! by @MikoE | Stardance
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MikoE
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Title: My awesome macropad! by @MikoE | Stardance
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1792928912.6237097
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1793792912.6237097
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4640
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AI Mix by @Akel | Stardance
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Akel
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0
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16.44
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[]
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[{"post_id": 56600, "ts": "202 [{"post_id": 56600, "ts": "2026-08-28T12:43:25Z", "hours": 16.4442, "text": "Minesweeper_v1.0 Learned how to use Knowledge base by building minesweeper AI | Finished Project 1B (cs50) check50: 25/25 style50: 0.99 hackatime: 6 hours"}]...
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Title: AI Mix by @Akel | Stardance
Devlogs:
Mines Title: AI Mix by @Akel | Stardance
Devlogs:
Minesweeper_v1.0 Learned how to use Knowledge base by building minesweeper AI | Finished Project 1B (cs50) check50: 25/25 style50: 0.99 hackatime: 6 hours...
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1792759945.0911336
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1793364745.0911336
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4641
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My awesome macropad! by @mihranrazaa | Stardance
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mihranrazaa
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Title: My awesome macropad! by @mihranrazaa | Star Title: My awesome macropad! by @mihranrazaa | Stardance...
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1793242360.5836143
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1793847160.5836143
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4642
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Zombie Survival Game by @Arush | Stardance
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Arush
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Title: Zombie Survival Game by @Arush | Stardance
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1793249377.9739223
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4643
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FetchIt by @QKing | Stardance
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QKing
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Title: FetchIt by @QKing | Stardance
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1793170567.3671284
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1793775367.3671284
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4644
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Zero-Assist by @Tan-May | Stardance
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Tan-May
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0
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229.35
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0
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[]
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[{"post_id": 40727, "ts": "202 [{"post_id": 40727, "ts": "2026-08-04T13:20:13Z", "hours": 13.7692, "text": "Check this out !! so yesterday i finished with the MCP implementation of the app , i implemented 4 transport method (STDIO,,HTTP,SSE and the LOCALHOST_STDIO) so when i was testing out i found out that only one of them is working properly , (the http one ) to which i connected multiple apps , mcp’s etc everything was working fine but when i tested the other transport method , not even a single one was working because it all needed the desktop to run with the specific packages so unfortunately i was not able to use it and i also find out about the nasa mcp where they daily upload the images mars rover images etc so i tried to test it but the problem was that the mcp was not http instead it was the STDIO so i was sad cause i had to fix first the mcp issue then test it but when i was in school in break i was getting board and opened the app and i had an idea like cant we just convert the normal stdio into the http mcp using the termux ? after asking to claude it said definitely we can do this so then i setuped the env(i will add a screenshot below ) and made a proxy server which converts the normal stdio mcp to the http steamtable and i was then able to access it locally using my app (i will add the image of it too) and i managed to connect to the mcp and fetch the images , now everything is working completely fine just the remaining part is the remaining transport which i will fix it some how !! also i will add some images i fetched below"}, {"post_id": 39007, "ts": "2026-08-01T17:30:37Z", "hours": 3.4689, "text": "Update !!! new devlog here … so now after doing some more research on the mcps and the implementation plans etc etc now im finally going all on it , ive added a ui component of the MCP in the Connection/Plugin/MCP , where i added few premade mcp options like (GitHub , brave search , external postgre sql etc ..) also there i added the option of the add custom server in which use can add custom server where currently the transport options are (STDIO,HTTP,SSE,LOCALHOST_STDIO (where you can add local mcp servers using the apps like termux etc ) so now that the ui is completed now i will move on to the connection part of the ui to the backend rust engine via uniffi )"}, {"post_id": 38224, "ts": "2026-07-31T14:56:23Z", "hours": 2.8122, "text": "Devlog time :> so now I’m continuing with the implementation of the MCP in the app like i previously talked now when i did some tinkering with the rust code using the ai , i managed to get all the connected MCP tools into the config file of the ai the config is getting updated now but the problem is that the config is constantly keeps changing don’t know what’s happening i guess the the problem is in the toml config generator which is glitching out , so now im trying fixing it from lots of time now , i guess i might have to use the antigravity to fix this but i exhausted my weekly limit cause I’m on a free tier 😭😭.. ill catch up with yall later till then bye bye 🙆.."}, {"post_id": 38050, "ts": "2026-07-31T07:21:16Z", "hours": 3.8936, "text": "Hello Hello Hello new devlog here , so now i started with the implementation of the MCP believe me guys once the app gets the MCP the app will go to another level , like it will then support literally any app (any app) it can perform actions like the mcp does but in simpler way also when i started with implementation i hit the problem again the code is there in the zeroclaw engine but again the problem is that its meant to run on the desktop so now we again have to do some changes in code and make the mcp run natively on the phone , i also found out some resources to do it like ( https://github.com/modelcontextprotocol/kotlin-sdk ) which is good so now the idea is something similar like shown in the screenshot below taken from the chat gpt …."}, {"post_id": 37593, "ts": "2026-07-30T13:01:48Z", "hours": 7.1106, "text": "Devlog here , so now i added the new cool animation (thinking orb ) this animation was totally inspired from the ( https://orbs.jakubantalik.com/ ) but the problem was that the orb was written in the typescript which wont work in our app cause our app is written in the kotlin so what i did was i downloaded the zip file from the repo pasted it to the claude and told him to convert it into kotlin for me and surprisingly the results was amazing , i will share the video recording too , and the other part i worked on was i added a few voices for my apps from the hugging face so now the user can use the custom voices too and also if he wants to use some of the default voices , the option is there do download in the app, some voices ( https://huggingface.co/rhasspy/piper-voices/resolve/main/en/en_US/lessac/medium/en_US-lessac-medium.onnx , https://huggingface.co/rhasspy/piper-voices/resolve/main/en/en_US/lessac/medium/en_US-lessac-medium.onnx , https://huggingface.co/rhasspy/piper-voices/resolve/main/en/en_GB/alan/medium/en_GB-alan-medium.onnx ) for someone whose interested …"}, {"post_id": 34542, "ts": "2026-07-25T10:46:59Z", "hours": 5.4758, "text": "Devlog: Google Workspace Integration This week I worked on integrating Google Workspace into Zero-Assist , allowing the AI to securely access services like Gmail, Google Drive, Google Docs, and Google Sheets after the user grants permission. The ZeroClaw engine already supports Google Workspace CLI (GWS) , but it was originally built for desktop Linux and expects a desktop environment with GWS already installed. Since Zero-Assist runs inside an Alpine Linux sandbox on Android using PRoot , that approach doesn’t work directly. Instead of rewriting the integration, I kept the existing architecture and adapted it for Android. What I Implemented I modified the sandbox installation process so that GWS is installed automatically whenever the user installs the standard sandbox packages. This means users don’t need to manually install or configure the CLI. Inside the app, I added a new Google Workspace plugin under: Connections → Plugins → Installed → Google Workspace When the user signs in, the Android app completes the OAuth flow and generates the required Google Workspace configuration files. To bridge Android and the Linux sandbox, I use the existing Android ↔ PRoot bridge . The plan is: User Login ↓ Android creates GWS credentials ↓ Credentials copied into PRoot sandbox ↓ Sandbox GWS CLI uses the same credentials ↓ AI can access approved Google services This keeps authentication native while allowing the Linux CLI to work without requiring the user to touch the terminal. Google Cloud Setup I also created a dedicated Google Cloud Console project for Zero-Assist. The project uses a Web Application OAuth client , which is required by the Google Workspace CLI authentication flow. I enabled the necessary APIs, including: Gmail API Google Drive API Google Docs API Google Sheets API More APIs can be enabled as additional integrations are added. Current Problem The authentication flow itself works correctly, and users can successfully sign in. The issue is that the generated credential/configuration files are not being copied correctly into the Linux sandbox . Because of this, the sandboxed GWS CLI cannot find the required authentication files, causing every Google Workspace command to fail. The current challenge isn’t OAuth—it’s reliably synchronizing credentials between Android and the PRoot environment. Once this bridge is working, users will simply sign in once, choose which Google services they want to grant access to, and Zero-Assist will be able to securely interact with those services without any manual setup. note:This devlog is written with hands and then passed to the chatgpt to format it with the .md because im very lazy to play with those colons and #’s"}, {"post_id": 33937, "ts": "2026-07-24T08:09:07Z", "hours": 6.6875, "text": "Device Control Development Update Yesterday I worked on expanding the Device Control system in my AI assistant. The idea behind this feature is to allow the AI to perform real actions on an Android device using the Accessibility Service . When the user gives a command such as “Subscribe to MrBeast on YouTube” , the main AI analyzes the request and delegates it to the Device Control tool. Current Workflow Launch the required application using: PackageManager.getLaunchIntentForPackage() startActivity() Capture a compressed screenshot of the current screen. Analyze the screenshot to identify UI elements and their screen coordinates. Navigate the interface and perform actions through the Android Accessibility APIs. Current Features Open applications Tap at (x, y) Swipe gestures Type text These core primitives allow the AI to interact with almost any Android application through UI automation. Future Improvements My main goals are to improve both speed and accuracy . Instead of navigating through multiple screens for simple system operations, I plan to add native high-level commands directly into the Device Control tool, such as: flashlight_toggle wifi_toggle bluetooth_toggle mobile_data_toggle volume_set brightness_set take_screenshot lock_screen open_notifications open_quick_settings go_home go_back open_recents These commands will allow the AI to execute common Android actions instantly without relying on visual navigation. For more complex tasks—such as interacting with third-party applications—the tool will continue using the screenshot + coordinate-based navigation pipeline. Long-Term Vision The goal is to build a hybrid Device Control system: Native commands for common Android operations (fast, reliable, and efficient). Vision-guided UI automation for complex interactions within any application. This architecture will significantly reduce execution time, improve reliability, and make the assistant capable of handling virtually any task on an Android device."}, {"post_id": 33134, "ts": "2026-07-22T19:18:54Z", "hours": 15.1933, "text": "So i basically went through the whole device control system and hardened it. the planner was splitting compound goals like “open instagram and message rohit” into separate calls which broke everything. also fixed it so the loop doesn’t just bail on the first response - it actually executes the action first. scroll was crashing if the planner didn’t send a direction so now it defaults down. and exceptions in the callback handler were just silently killing the process so now everything is caught and logged properly. added loop detection so it doesn’t get stuck repeating the same thing, post-action screen verification, and 44 tests to cover it all. very happy that it worked , it took lots of time but eventually i think the results are very very good though this thing not works great on the local ai’s but with the cheap api like openrouter/free , this thing can give pretty good results"}, {"post_id": 32219, "ts": "2026-07-21T07:52:35Z", "hours": 20.9892, "text": "okay so after spending lots of time on this issue , im finally able to make this work again , the problem was that (bin/sh, ust/bin/env) never extracted because of one code issue where i accidently mentioned them as the read only memory in the apps storage so the distro was installing also getting extracted but becacuse of the read only type of file , the app was not able to perform any actions on it , so now after taking the help from the open code now the sandbox is fully functional and working on every devices , also ive added some default packages which will get installed during the setup of the sandbox such as (wget, git , python3, jq, py3-pip, nodejs ,lftp and the openssh-client) just using the single command (apk add –no-cache bash curl wget git jq python3 py3-pip nodejs openssh-client lftp rsync)"}, {"post_id": 30521, "ts": "2026-07-18T05:11:12Z", "hours": 13.5486, "text": "Hello guys, devlog here!I finally got the Linux sandbox in Zero-Assist working end-to-end! The sandbox runs Alpine Linux through PRoot directly on Android without requiring root.Getting it working was harder than expected, though. I ran into several Android-specific issues.Fixing the SandboxThe first problem was Alpine’s heavy use of BusyBox hardlinks. My TAR extractor used File.copyTo(), which didn’t preserve executable permissions, causing errors like:proot error: execve(“/bin/sh”): Permission denied I fixed this by preserving executable bits:linkTarget.copyTo(outFile, overwrite = true) if (linkTarget.canExecute()) { outFile.setExecutable(true, false) } Some hardlinks were also extracted before BusyBox itself, so I added a second repair pass after extraction to restore critical commands like /bin/sh, /bin/ls, and /bin/cat.Symlinks were another problem because Android can block their creation. I added a fallback that copies the target when creating the actual symlink fails:try { Files.createSymbolicLink(outFile.toPath(), Paths.get(linkName)) } catch (e: Exception) { fallback.copyTo(outFile, overwrite = true) } I also had problems directly executing PRoot because some Android app directories can be noexec. The solution was to launch PRoot through Android’s system linker:val args = arrayOf( “/system/bin/linker64”, prootPath, “–rootfs=$rootfsPath”, “/bin/sh”, “-c”, command ) I also added corrupted download detection and automatic Alpine mirror fallback, making the rootfs installation much more reliable.Giving the AI Linux ToolsAfter getting the sandbox stable, I added two AI tools:sandbox_execute — Executes commands inside Alpine and supports persistent shell state, working directories, environment variables, timeouts, and background processes.sandbox_manage_process — Lets the AI list, monitor, read logs from, and kill background processes.For example, the AI can execute:{ “command”: “python3 –version && uname -a”, “working_dir”: “/root” } Or start a background server:{ “command”: “python3 -m http.server 8000”, “background”: true } The execution pipeline now looks like:AI Agent ↓ Rust Tool Layer ↓ Authenticated Local HTTP Bridge ↓ Kotlin Sandbox Manager ↓ PRoot ↓ Alpine Linux The Rust runtime communicates with the Kotlin sandbox through a localhost bridge on 127.0.0.1:49481, protected by a randomly generated per-process bearer token.And now the sandbox is fully functional end-to-end!The AI can execute real Linux commands, install packages, maintain persistent shell sessions, run scripts, start background processes, inspect their logs, and manage them — all inside Alpine Linux running directly on Android without root.This was one of the hardest parts of Zero-Assist so far, but now the AI finally has its own real Linux environment to work with."}, {"post_id": 29333, "ts": "2026-07-16T06:39:51Z", "hours": 11.0894, "text": "Giving Zero-Assist Its Own Linux Sandbox A lot of features I want in Zero-Assist need actual Linux tools: shell commands, Python, Git, Node.js, CLI tools, etc. I didn’t want this to require root, so I built a local Alpine Linux sandbox using PRoot that runs entirely on-device. The architecture is basically: AI daemon → sandbox tool → HTTP bridge → Kotlin sandbox manager → PRoot → Alpine Getting PRoot running One annoying problem was Android’s noexec restrictions. PRoot is stored inside the app’s data/native library directory and can’t always be executed normally. The solution was launching it through Android’s dynamic linker: private fun buildProcessArgs ( command : String , workingDir : String ): Array < String > { val args = arrayOf ( prootPath , \"--rootfs=$rootfsPath\" , \"--bind=/dev\" , \"--bind=/proc\" , \"--bind=/sys\" , \"--bind=$homePath:/root\" , \"--bind=$tmpPath:/tmp\" , \"-0\" , \"-w\" , workingDir , \"/bin/sh\" , \"-c\" , command ) return if ( ANDROID_LINKER != null ) arrayOf ( ANDROID_LINKER , * args ) else args } So commands effectively go through: /system/bin/linker64 → PRoot → Alpine → command This lets the bundled PRoot code run despite the noexec restriction. Connecting Rust and Kotlin My AI daemon is written in Rust, while the sandbox is managed by Kotlin. I connected them using a small NanoHTTPD server running only on localhost. return when ( session . uri ) { \"/health\" -> handleHealth () \"/execute\" -> handleExecute ( session ) \"/manage_process\" -> handleManageProcess ( session ) else -> errorJson ( Response . Status . NOT_FOUND , \"Unknown path: ${session.uri}\" ) } The Rust daemon sends authenticated requests to 127.0.0.1:49481 . The AI currently gets two tools: sandbox_execute - run Linux commands sandbox_manage_process - manage background processes Persistent shell sessions I wanted the sandbox to behave like an actual terminal instead of starting from scratch for every command. If the AI runs: cd /root/project export TEST = hello the next tool call stays in /root/project and keeps the environment variable. Each conversation gets a separate persistent shell: Conversation A → Shell A Conversation B → Shell B This keeps cwd/environment state while preventing different conversations from affecting each other. Background commands are isolated differently. Each one gets a separate PRoot executor and is tracked by a process manager. The AI can start a long-running command, continue doing other things, then check its logs or kill it later. Installing Alpine The sandbox manager handles the full setup: Download Alpine → Extract → Fix hardlinks/permissions → apk update → Install tools → Ready The hardlink fix was needed because some Alpine tar entries reference files that haven’t been extracted yet, which caused extraction failures on Android. Right now the sandbox comes with Bash, Python + pip, Node.js, Git, curl, wget, jq, SSH, lftp and rsync. The main parts are: ProotExecutor - executes commands LinuxSandboxManager - lifecycle/setup SandboxBridgeServer - Rust ↔ Kotlin bridge SandboxProcessManager - background processes PersistentSandboxShell - per-conversation shell state There is still more I want to improve, especially filesystem sharing, networking and reliability for longer agent tasks. But the main system is finally working: Zero-Assist can now give an AI agent a real Linux userspace running locally inside an Android app without requiring root. This started with the idea of somehow giving the AI a tiny Linux computer inside the app. Now it actually has one."}, {"post_id": 28451, "ts": "2026-07-14T18:16:53Z", "hours": 4.185, "text": "Giving My Android AI App Its Own Linux Sandbox One of the biggest problems with my app was that a lot of the features I wanted to build actually needed a real desktop environment. Things like: Running shell commands Browser automation Using desktop CLI tools Installing packages on demand Running scripts ZeroClaw already supports these kinds of capabilities, but on Android I couldn’t really use them to their full potential. The app simply didn’t have an environment that could support everything properly. So I decided… Why not give the app its own minimal Linux desktop? The Initial Research Luckily, I already had some experience with Linux. I had previously played around with: Linux distros PRoot chroot Minimal desktop environments So I started looking at every possible approach. Option 1 — Android’s default shell At first I thought about using the shell that every Android app already gets. It looked simple. But after experimenting with it, I realized it was missing a lot of the commands and tools I actually needed. That completely defeated the purpose of having a proper sandbox. So I dropped that idea. Option 2 — chroot Next I started researching chroot. Honestly, from a technical point of view, chroot is amazing. It gets extremely close to a real Linux environment. Performance is great and it behaves much more like an actual desktop installation. There was only one problem. It requires a rooted device. That was an immediate deal breaker. I don’t want someone to root their phone just to use my app. So chroot was out too. Option 3 — PRoot After a lot of brainstorming, reading documentation, and trying different ideas, I finally settled on PRoot. It isn’t perfect. There are still some limitations compared to a real Linux installation, but I’ll talk about those another time. The important part is this: No root required Works on normal Android devices Can run a real Linux userspace Supports the tools my AI actually needs For what I’m trying to build, it was the best balance. Choosing the distro I wanted something lightweight. Really lightweight. So I picked Alpine Linux . The base image is around 5 MB . Yes… Literally 5 MB. After installing the packages I consider “essential” for the AI (things like Python, pip, curl, git, etc.), the whole environment comes to roughly 700 MB . That gives the AI a solid starting point without making users download multiple gigabytes on day one. If more tools are needed later, the AI can simply install them inside the sandbox. Current Progress I’ve finally started implementing everything. So far I’ve added: sandbox_client.rs sandbox_main.kt Configuration files for the sandbox Default package lists that will be installed automatically There’s still a lot left to build, but the foundation is finally there. This is probably one of the biggest architectural changes I’ve made to the app so far. Instead of trying to force Android to behave like a desktop, I’m giving the AI its own Linux environment that it can actually work inside. Still a long way to go !!! MAKE SURE TO FOLLOW THE PROJECT YES THE IMAGE IS AI GENETRATED , BUT I DIDNT KNOW WHAT TO DO FOR BETTER EXPLAINATION SO I DID IT :D"}, {"post_id": 25882, "ts": "2026-07-10T11:26:04Z", "hours": 11.9064, "text": "After long time … hello guys making this devlog after very long time , i had an issue ,when i was cleaning up my project , removing the dead code and optimizing the app where i was taking the help of the antigravity for this , i accidently deleted the hardware side in the zero claw (engine of zero assist) which was in beta i was just remaining to test it because i didn’t have any proper hardware to do it so it was remaining to test and unfortunately i didn’t even had the code pushed on the GitHub which made the situation worst so now I’ve nearly fixed it , the app is successfully building properly and now I’ve decided to push the code every day if possible on the GitHub to avoid this type of things and I’m writing this devlog because of the new rule i came by where only 10 hrs. will be counted MY BAD LUCK now my 12 hrs. are going to waste 😭😭because i was not uploading the devlog and the time increased so uploading this asap so that my next time will be counted !!"}, {"post_id": 12384, "ts": "2026-06-20T06:53:41Z", "hours": 26.2319, "text": "Devlog #8 — Zero-Assist I added a Skills Section to Zero-Assist, and it’s probably one of the more useful things we’ve shipped so far. What It Is Skills are installable modules built by the Zeroclaw community that extend what the app can do. Things like Doc Writer, Auto-Coder, and more — each one teaches the app how to handle a specific type of task better. Install one, and Zero-Assist reads it and starts applying it automatically. No setup, no configuration, just tap and it works. These aren’t shortcuts or preset prompts. The app actually understands the skill and uses it to make smarter decisions when you’re working. Always Growing The library isn’t static. The community keeps adding new skills and updating existing ones, so the app naturally gets more capable over time without needing a big update from our end. Whatever gets added is available to you immediately. Big thanks to everyone in the Zeroclaw community who built and contributed skills — this whole section runs on your work. What’s Next We’re making it easier for more people to submit skills, and we’re looking at adding ratings and changelogs so you can track what’s new and what’s worth installing. More soon."}, {"post_id": 9693, "ts": "2026-06-16T03:16:35Z", "hours": 2.8722, "text": "Devlog #7 — Multi-Agent Architecture & Custom Agent Builder Zero-Assist just got a major upgrade. What if instead of one AI assistant, you had an entire team of AI specialists working together? That’s exactly what I’ve built. Multiple Agent System Zero-Assist now supports multiple specialized agents, each optimized for a specific role and workflow. Master Agent The brain of the operation. Orchestrates all agents Assigns tasks intelligently Monitors progress Routes requests to the best agent Researcher Agent Your personal information hunter. Searches the web Collects and analyzes data Returns structured insights Filters noise and focuses on relevant information Coder Agent Built for developers. Writes code Reviews code Fixes bugs Assists with architecture and implementation Planner Agent Turns chaos into clarity. Breaks down goals Creates actionable roadmaps Generates timelines Organizes complex projects Custom Agent Builder The most exciting feature in this update. You can now create your own specialized AI agents with just a few clicks. Customize: System Prompt Temperature Tags & Capabilities LLM Model Agent Role & Personality Want an AI Startup Advisor? Create one. Want a Bug-Hunting Expert? Create one. Want a Cybersecurity Specialist? Create one. The possibilities are endless. Why This Matters Most AI applications rely on a single model trying to do everything. Zero-Assist takes a different approach. Instead of one assistant, you get an entire ecosystem of AI specialists that can collaborate, delegate tasks, and work together to solve problems more efficiently. Each agent has: Its own configuration Its own expertise Its own behavior Its own model settings This creates a more scalable and intelligent workflow compared to traditional AI assistants. Vision The long-term goal isn’t just to build another chatbot. It’s to build an AI Operating System where users can create, orchestrate, and manage teams of intelligent agents that work together to accomplish complex tasks. And this is only the beginning. Screenshot attached below."}, {"post_id": 9256, "ts": "2026-06-15T15:22:43Z", "hours": 22.2608, "text": "#Devlog 6 -Zero-Assist Shipped a big update today. The app can now handle complex tasks much more reliably, and tools run in parallel instead of sequentially — so heavy workloads finish noticeably faster without the app choking midway. The smarter behavior actually came from Trimming down the soul.md, longterm-memory.md, agents.md, and user.md files reduced token usage significantly, and the model started reasoning better almost immediately. I tested it across several complex tasks and the output quality genuinely caught me off guard — results I didn’t expected!!! Voice has been a pain point for a while. Dug into the Piper latency issues, restructured the integration, and the pipeline is much smoother now. Still sounds robotic — that’s a problem I haven’t cracked yet — but the lag that made it frustrating to use is mostly gone. Overall the app feels like a different version of itself. More capable, leaner, and faster. Dropping Demo vid of the test runs below so you can see what it’s actually doing now. here is demo video too : https://youtube.com/shorts/F8sLD21dcWo"}, {"post_id": 6943, "ts": "2026-06-11T17:21:14Z", "hours": 15.2497, "text": "Devlog 5 – Channel Integration and Tool Access Today I spent most of my time working on one of the biggest features of the project so far: Channel Integration . The channels system already supports multiple platforms such as Telegram, WhatsApp, Slack, Discord, and several others. My goal was to connect these channels with the assistant so that it can interact with users across different platforms while still having access to the tools and capabilities available on the phone. To achieve this, I worked on properly connecting the Rust bridge with the Kotlin application. Once the communication layer was working correctly, I was able to expose several powerful capabilities to the assistant, including: Access to phone storage and files Accessibility-based device control Web tools and online actions Composio integrations File management and manipulation Cross-platform channel communication Various assistant tools that were previously isolated from each other This was a fairly complex task because multiple systems needed to communicate reliably. I also used AI assistance throughout the development process to help debug issues, validate approaches, and speed up implementation. In total, this work took roughly 12 hours . At the moment, I have not pushed the code to the repository because the feature still requires extensive testing. Since it touches storage access, tool execution, and communication across multiple services, I want to ensure everything is stable before making it public. Once I complete the testing phase, I will push the implementation to the repository. This feature significantly expands what the application can do. Instead of being just a chatbot, it is evolving into a full assistant platform capable of interacting with external services, managing files, controlling parts of the device, and communicating through multiple messaging platforms. The long-term vision is to create a system where users can build highly capable personal assistants that can perform real tasks rather than simply generate text. There is still a lot more work ahead, but today’s progress was a major step toward that goal. Stay tuned—some very exciting features are currently in development."}, {"post_id": 5481, "ts": "2026-06-09T09:01:08Z", "hours": 12.9753, "text": "Zero-Assist Devlog #4 — The Phone Is Now a Personal Chat Server so Devlog 4 is here. The main thing i fixed this time is the channels section of the app. channels are basically how Zero-Assist can gets input or give output to other app — like Telegram, WhatsApp, and other messaging apps. once you connect them, the app starts listening. but whats different now that channels are working, the phone isn’t just an AI assistant anymore. it’s your personal home server that you can message like a real in-person. what this actually means in practice: say you’re away and you message your own Telegram bot: “water the plants” — Zero-Assist picks that up, figures out what you mean, and either goes with an MQTT signal to your smart home setup or directly talks to your microcontroller over USB or BLE , whichever is available. no extra apps, no cloud, just your phone doing the work. same idea works for your homelab. you can message “ping my website” and the app will run the actual shell command on your phone and report back. this does need a one-time manual connection to set up, but after that it just works. basically the phone becomes a chat-controlled home automation that you own fully here is no cloud included except the llm , which you can also use the local llm . what i’m planning to add next: i’m planning a live dashboard screen for this — not raw logs, but a simplified readable feed. something like: “message received via Telegram → running plant watering command → sent MQTT signal ✓” the idea is it’s useful for people who like seeing what’s happening here, but written in plain language instead of technical stuff for the normal users . the hard part this time was : most of the time on this devlog went into connecting the Rust backend (which handles all the channel logic) to the Kotlin front-end of the app , so getting them to work together cleanly took a lot of debugging and was honestly the most frustrating part of this whole update. got it working though. more soon."}, {"post_id": 4198, "ts": "2026-06-07T12:47:20Z", "hours": 7.8933, "text": "devlog -3 added a new shared folder option int the app so that the app can share the storage from phone , it can open files edit files , manipulate the files and do lots of stuff with it , added the screenshot below"}, {"post_id": 3507, "ts": "2026-06-06T14:09:20Z", "hours": 18.2539, "text": "Devlog #2 is here!! so after the piper TTS update in devlog #1, I’ve been working on something way bigger — I added Composio integration to Zero-Assist for those who don’t know what composio is — it’s basically a platform that connects AI agents to over 1,000 apps like Gmail, Slack, GitHub, Notion, Salesforce, Google Drive and a lot more. think of it as the bridge between your AI and the rest of the internet. so now Zero-Assist can actually do things for you like — → send and read messages (if you give it the right permissions) → make notes in Notion automatically → send mails on your behalf → store your files to Google Drive → and a lot more depending on which apps you connect the best part is this feature was already there inside ZeroClaw (which is what Zero-Assist is built on), so it wasn’t built from scratch — it was more about bringing it properly into the Android app and making it actually usable. check out the video ( https://drive.google.com/file/d/1ZO56Ekrq7fu205Epqx8fH-Vkt_E5xc16/view?usp=sharing ) for a small demo of how it works"}, {"post_id": 1568, "ts": "2026-06-03T17:45:24Z", "hours": 3.4811, "text": "ZERO-ASSIST devlog 1 IM working on Zero-Assist voice assistant app on which im already working from March , the app has lots of features , i completely vibe coded the app but now im working on the finishing part of the app so today i improve the voice assist mode , the voice was really slow on cheaper Android phones. When you spoke to it, you’d wait 10+ seconds before hearing the voice response. What I fixed today 1️⃣ Made It Stop Waiting So Long Before: App waited up to 2.5-5 seconds to make sure the TTS Engine was ready Now: Only waits 0.9-1.8 seconds Result: Faster feedback !! You can also check the app here ( https://github.com/Tanmay-1122/Zero-Assist )"}]...
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Title: Zero-Assist by @Tan-May | Stardance
Devlog Title: Zero-Assist by @Tan-May | Stardance
Devlogs:
ZERO-ASSIST devlog 1 IM working on Zero-Assist voice assistant app on which im already working from March , the app has lots of features , i completely vibe coded the app but now im working on the finishing part of the app so today i improve the voice assist mode , the voice was really slow on cheaper Android phones. When you spoke to it, you’d wait 10+ seconds before hearing the voice response. What I fixed today 1️⃣ Made It Stop Waiting So Long Before: App waited up to 2.5-5 seconds to make sure the TTS Engine was ready Now: Only waits 0.9-1.8 seconds Result: Faster feedback !! You can also check the app here ( https://github.com/Tanmay-1122/Zero-Assist )
Devlog #2 is here!! so after the piper TTS update in devlog #1, I’ve been working on something way bigger — I added Composio integration to Zero-Assist for those who don’t know what composio is — it’s basically a platform that connects AI agents to over 1,000 apps like Gmail, Slack, GitHub, Notion, Salesforce, Google Drive and a lot more. think of it as the bridge between your AI and the rest of the internet. so now Zero-Assist can actually do things for you like — → send and read messages (if you give it the right permissions) → make notes in Notion automatically → send mails on your behalf → store your files to Google Drive → and a lot more depending on which apps you connect the best part is this feature was already there inside ZeroClaw (which is what Zero-Assist is built on), so it wasn’t built from scratch — it was more about bringing it properly into the Android app and making it actually usable. check out the video ( https://drive.google.com/file/d/1ZO56Ekrq7fu205Epqx8fH-Vkt_E5xc16/view?usp=sharing ) for a small demo of how it works
devlog -3 added a new shared folder option int the app so that the app can share the storage from phone , it can open files edit files , manipulate the files and do lots of stuff with it , added the screenshot below
Zero-Assist Devlog #4 — The Phone Is Now a Personal Chat Server so Devlog 4 is here. The main thing i fixed this time is the channels section of the app. channels are basically how Zero-Assist can gets input or give output to other app — like Telegram, WhatsApp, and other messaging apps. once you connect them, the app starts listening. but whats different now that channels are working, the phone isn’t just an AI assistant anymore. it’s your personal home server that you can message like a real in-person. what this actually means in practice: say you’re away and you message your own Telegram bot: “water the plants” — Zero-Assist picks that up, figures out what you mean, and either goes with an MQTT signal to your smart home setup or directly talks to your microcontroller over USB or BLE , whichever is available. no extra apps, no cloud, just your phone doing the work. same idea works for your homelab. you can message “ping my website” and the app will run the actual shell command on your phone and report back. this does need a one-time manual connection to set up, but after that it just works. basically the phone becomes a chat-controlled home automation that you own fully here is no cloud included except the llm , which you can also use the local llm . what i’m planning to add next: i’m planning a live dashboard screen for this — not raw logs, but a simplified readable feed. something like: “message received via Telegram → running plant watering command → sent MQTT signal ✓” the idea is it’s useful for people who like seeing what’s happening here, but written in plain language instead of technical stuff for the normal users . the hard part this time was : most of the time on this devlog went into connecting the Rust backend (which handles all the channel logic) to the Kotlin front-end of the app , so getting them to work together cleanly took a lot of debugging and was honestly the most frustrating part of this whole update. got it working though. more soon.
Devlog 5 – Channel Integration and Tool Access Today I spent most of my time working on one of the biggest features of the project so far: Channel Integration . The channels system already supports multiple platforms such as Telegram, WhatsApp, Slack, Discord, and several others. My goal was to connect these channels with the assistant so that it can interact with users across different platforms while still having access to the tools and capabilities available on the phone. To achieve this, I worked on properly connecting the Rust bridge with the Kotlin application. Once the communication layer was working correctly, I was able to expose several powerful capabilities to the assistant, including: Access to phone storage and files Accessibility-based device control Web tools and online actions Composio integrations File management and manipulation Cross-platform channel communication Various assistant tools that were previously isolated from each other This was a fairly complex task because multiple systems needed to communicate reliably. I also used AI assistance throughout the development process to help debug issues, validate approaches, and speed up implementation. In total, this work took roughly 12 hours . At the moment, I have not pushed the code to the repository because the feature still requires extensive testing. Since it touches storage access, tool execution, and communication across multiple services, I want to ensure everything is stable before making it public. Once I complete the testing phase, I will push the implementation to the repository. This feature significantly expands what the application can do. Instead of being just a chatbot, it is evolving into a full assistant platform capable of interacting with external services, managing files, controlling parts of the device, and communicating through multiple messaging platforms. The long-term vision is to create a system where users can build highly capable personal assistants that can perform real tasks rather than simply generate text. There is still a lot more work ahead, but today’s progress was a major step toward that goal. Stay tuned—some very exciting features are currently in development.
#Devlog 6 -Zero-Assist Shipped a big update today. The app can now handle complex tasks much more reliably, and tools run in parallel instead of sequentially — so heavy workloads finish noticeably faster without the app choking midway. The smarter behavior actually came from Trimming down the soul.md, longterm-memory.md, agents.md, and user.md files reduced token usage significantly, and the model started reasoning better almost immediately. I tested it across several complex tasks and the output quality genuinely caught me off guard — results I didn’t expected!!! Voice has been a pain point for a while. Dug into the Piper latency issues, restructured the integration, and the pipeline is much smoother now. Still sounds robotic — that’s a problem I haven’t cracked yet — but the lag that made it frustrating to use is mostly gone. Overall the app feels like a different version of itself. More capable, leaner, and faster. Dropping Demo vid of the test runs below so you can see what it’s actually doing now. here is demo video too : https://youtube.com/shorts/F8sLD21dcWo
Devlog #7 — Multi-Agent Architecture & Custom Agent Builder Zero-Assist just got a major upgrade. What if instead of one AI assistant, you had an entire team of AI specialists working together? That’s exactly what I’ve built. Multiple Agent System Zero-Assist now supports multiple specialized agents, each optimized for a specific role and workflow. Master Agent The brain of the operation. Orchestrates all agents Assigns tasks intelligently Monitors progress Routes requests to the best agent Researcher Agent Your personal information hunter. Searches the web Collects and analyzes data Returns structured insights Filters noise and focuses on relevant information Coder Agent Built for developers. Writes code Reviews code Fixes bugs Assists with architecture and implementation Planner Agent Turns chaos into clarity. Breaks down goals Creates actionable roadmaps Generates timelines Organizes complex projects Custom Agent Builder The most exciting feature in this update. You can now create your own specialized AI agents with just a few clicks. Customize: System Prompt Temperature Tags & Capabilities LLM Model Agent Role & Personality Want an AI Startup Advisor? Create one. Want a Bug-Hunting Expert? Create one. Want a Cybersecurity Specialist? Create one. The possibilities are endless. Why This Matters Most AI applications rely on a single model trying to do everything. Zero-Assist takes a different approach. Instead of one assistant, you get an entire ecosystem of AI specialists that can collaborate, delegate tasks, and work together to solve problems more efficiently. Each agent has: Its own configuration Its own expertise Its own behavior Its own model settings This creates a more scalable and intelligent workflow compared to traditional AI assistants. Vision The long-term goal isn’t just to build another chatbot. It’s to build an AI Operating System where users can create, orchestrate, and manage teams of intelligent agents that work together to accomplish complex tasks. And this is only the beginning. Screenshot attached below.
Devlog #8 — Zero-Assist I added a Skills Section to Zero-Assist, and it’s probably one of the more useful things we’ve shipped so far. What It Is Skills are installable modules built by the Zeroclaw community that extend what the app can do. Things like Doc Writer, Auto-Coder, and more — each one teaches the app how to handle a specific type of task better. Install one, and Zero-Assist reads it and starts applying it automatically. No setup, no configuration, just tap and it works. These aren’t shortcuts or preset prompts. The app actually understands the skill and uses it to make smarter decisions when you’re working. Always Growing The library isn’t static. The community keeps adding new skills and updating existing ones, so the app naturally gets more capable over time without needing a big update from our end. Whatever gets added is available to you immediately. Big thanks to everyone in the Zeroclaw community who built and contributed skills — this whole section runs on your work. What’s Next We’re making it easier for more people to submit skills, and we’re looking at adding ratings and changelogs so you can track what’s new and what’s worth installing. More soon.
After long time … hello guys making this devlog after very long time , i had an issue ,when i was cleaning up my project , removing the dead code and optimizing the app where i was taking the help of the antigravity for this , i accidently deleted the hardware side in the zero claw (engine of zero assist) which was in beta i was just remaining to test it because i didn’t have any proper hardware to do it so it was remaining to test and unfortunately i didn’t even had the code pushed on the GitHub which made the situation worst so now I’ve nearly fixed it , the app is successfully building properly and now I’ve decided to push the code every day if possible on the GitHub to avoid this type of things and I’m writing this devlog because of the new rule i came by where only 10 hrs. will be counted MY BAD LUCK now my 12 hrs. are going to waste 😭😭because i was not uploading the devlog and the time increased so uploading this asap so that my next time will be counted !!
Giving My Android AI App Its Own Linux Sandbox One of the biggest problems with my app was that a lot of the features I wanted to build actually needed a real desktop environment. Things like: Running shell commands Browser automation Using desktop CLI tools Installing packages on demand Running scripts ZeroClaw already supports these kinds of capabilities, but on Android I couldn’t really use them to their full potential. The app simply didn’t have an environment that could support everything properly. So I decided… Why not give the app its own minimal Linux desktop? The Initial Research Luckily, I already had some experience with Linux. I had previously played around with: Linux distros PRoot chroot Minimal desktop environments So I started looking at every possible approach. Option 1 — Android’s default shell At first I thought about using the shell that every Android app already gets. It looked simple. But after experimenting with it, I realized it was missing a lot of the commands and tools I actually needed. That completely defeated the purpose of having a proper sandbox. So I dropped that idea. Option 2 — chroot Next I started researching chroot. Honestly, from a technical point of view, chroot is amazing. It gets extremely close to a real Linux environment. Performance is great and it behaves much more like an actual desktop installation. There was only one problem. It requires a rooted device. That was an immediate deal breaker. I don’t want someone to root their phone just to use my app. So chroot was out too. Option 3 — PRoot After a lot of brainstorming, reading documentation, and trying different ideas, I finally settled on PRoot. It isn’t perfect. There are still some limitations compared to a real Linux installation, but I’ll talk about those another time. The important part is this: No root required Works on normal Android devices Can run a real Linux userspace Supports the tools my AI actually needs For what I’m trying to build, it was the best balance. Choosing the distro I wanted something lightweight. Really lightweight. So I picked Alpine Linux . The base image is around 5 MB . Yes… Literally 5 MB. After installing the packages I consider “essential” for the AI (things like Python, pip, curl, git, etc.), the whole environment comes to roughly 700 MB . That gives the AI a solid starting point without making users download multiple gigabytes on day one. If more tools are needed later, the AI can simply install them inside the sandbox. Current Progress I’ve finally started implementing everything. So far I’ve added: sandbox_client.rs sandbox_main.kt Configuration files for the sandbox Default package lists that will be installed automatically There’s still a lot left to build, but the foundation is finally there. This is probably one of the biggest architectural changes I’ve made to the app so far. Instead of trying to force Android to behave like a desktop, I’m giving the AI its own Linux environment that it can actually work inside. Still a long way to go !!! MAKE SURE TO FOLLOW THE PROJECT YES THE IMAGE IS AI GENETRATED , BUT I DIDNT KNOW WHAT TO DO FOR BETTER EXPLAINATION SO I DID IT :D
Giving Zero-Assist Its Own Linux Sandbox A lot of features I want in Zero-Assist need actual Linux tools: shell commands, Python, Git, Node.js, CLI tools, etc. I didn’t want this to require root, so I built a local Alpine Linux sandbox using PRoot that runs entirely on-device. The architecture is basically: AI daemon → sandbox tool → HTTP bridge → Kotlin sandbox manager → PRoot → Alpine Getting PRoot running One annoying problem was Android’s noexec restrictions. PRoot is stored inside the app’s data/native library directory and can’t always be executed normally. The solution was launching it through Android’s dynamic linker: private fun buildProcessArgs ( command : String , workingDir : String ): Array < String > { val args = arrayOf ( prootPath , "--rootfs=$rootfsPath" , "--bind=/dev" , "--bind=/proc" , "--bind=/sys" , "--bind=$homePath:/root" , "--bind=$tmpPath:/tmp" , "-0" , "-w" , workingDir , "/bin/sh" , "-c" , command ) return if ( ANDROID_LINKER != null ) arrayOf ( ANDROID_LINKER , * args ) else args } So commands effectively go through: /system/bin/linker64 → PRoot → Alpine → command This lets the bundled PRoot code run despite the noexec restriction. Connecting Rust and Kotlin My AI daemon is written in Rust, while the sandbox is managed by Kotlin. I connected them using a small NanoHTTPD server running only on localhost. return when ( session . uri ) { "/health" -> handleHealth () "/execute" -> handleExecute ( session ) "/manage_process" -> handleManageProcess ( session ) else -> errorJson ( Response . Status . NOT_FOUND , "Unknown path: ${session.uri}" ) } The Rust daemon sends authenticated requests to 127.0.0.1:49481 . The AI currently gets two tools: sandbox_execute - run Linux commands sandbox_manage_process - manage background processes Persistent shell sessions I wanted the sandbox to behave like an actual terminal instead of starting from scratch for every command. If the AI runs: cd /root/project export TEST = hello the next tool call stays in /root/project and keeps the environment variable. Each conversation gets a separate persistent shell: Conversation A → Shell A Conversation B → Shell B This keeps cwd/environment state while preventing different conversations from affecting each other. Background commands are isolated differently. Each one gets a separate PRoot executor and is tracked by a process manager. The AI can start a long-running command, continue doing other things, then check its logs or kill it later. Installing Alpine The sandbox manager handles the full setup: Download Alpine → Extract → Fix hardlinks/permissions → apk update → Install tools → Ready The hardlink fix was needed because some Alpine tar entries reference files that haven’t been extracted yet, which caused extraction failures on Android. Right now the sandbox comes with Bash, Python + pip, Node.js, Git, curl, wget, jq, SSH, lftp and rsync. The main parts are: ProotExecutor - executes commands LinuxSandboxManager - lifecycle/setup SandboxBridgeServer - Rust ↔ Kotlin bridge SandboxProcessManager - background processes PersistentSandboxShell - per-conversation shell state There is still more I want to improve, especially filesystem sharing, networking and reliability for longer agent tasks. But the main system is finally working: Zero-Assist can now give an AI agent a real Linux userspace running locally inside an Android app without requiring root. This started with the idea of somehow giving the AI a tiny Linux computer inside the app. Now it actually has one.
Hello guys, devlog here!I finally got the Linux sandbox in Zero-Assist working end-to-end! The sandbox runs Alpine Linux through PRoot directly on Android without requiring root.Getting it working was harder than expected, though. I ran into several Android-specific issues.Fixing the SandboxThe first problem was Alpine’s heavy use of BusyBox hardlinks. My TAR extractor used File.copyTo(), which didn’t preserve executable permissions, causing errors like:proot error: execve(“/bin/sh”): Permission denied I fixed this by preserving executable bits:linkTarget.copyTo(outFile, overwrite = true) if (linkTarget.canExecute()) { outFile.setExecutable(true, false) } Some hardlinks were also extracted before BusyBox itself, so I added a second repair pass after extraction to restore critical commands like /bin/sh, /bin/ls, and /bin/cat.Symlinks were another problem because Android can block their creation. I added a fallback that copies the target when creating the actual symlink fails:try { Files.createSymbolicLink(outFile.toPath(), Paths.get(linkName)) } catch (e: Exception) { fallback.copyTo(outFile, overwrite = true) } I also had problems directly executing PRoot because some Android app directories can be noexec. The solution was to launch PRoot through Android’s system linker:val args = arrayOf( “/system/bin/linker64”, prootPath, “–rootfs=$rootfsPath”, “/bin/sh”, “-c”, command ) I also added corrupted download detection and automatic Alpine mirror fallback, making the rootfs installation much more reliable.Giving the AI Linux ToolsAfter getting the sandbox stable, I added two AI tools:sandbox_execute — Executes commands inside Alpine and supports persistent shell state, working directories, environment variables, timeouts, and background processes.sandbox_manage_process — Lets the AI list, monitor, read logs from, and kill background processes.For example, the AI can execute:{ “command”: “python3 –version && uname -a”, “working_dir”: “/root” } Or start a background server:{ “command”: “python3 -m http.server 8000”, “background”: true } The execution pipeline now looks like:AI Agent ↓ Rust Tool Layer ↓ Authenticated Local HTTP Bridge ↓ Kotlin Sandbox Manager ↓ PRoot ↓ Alpine Linux The Rust runtime communicates with the Kotlin sandbox through a localhost bridge on 127.0.0.1:49481, protected by a randomly generated per-process bearer token.And now the sandbox is fully functional end-to-end!The AI can execute real Linux commands, install packages, maintain persistent shell sessions, run scripts, start background processes, inspect their logs, and manage them — all inside Alpine Linux running directly on Android without root.This was one of the hardest parts of Zero-Assist so far, but now the AI finally has its own real Linux environment to work with.
okay so after spending lots of time on this issue , im finally able to make this work again , the problem was that (bin/sh, ust/bin/env) never extracted because of one code issue where i accidently mentioned them as the read only memory in the apps storage so the distro was installing also getting extracted but becacuse of the read only type of file , the app was not able to perform any actions on it , so now after taking the help from the open code now the sandbox is fully functional and working on every devices , also ive added some default packages which will get installed during the setup of the sandbox such as (wget, git , python3, jq, py3-pip, nodejs ,lftp and the openssh-client) just using the single command (apk add –no-cache bash curl wget git jq python3 py3-pip nodejs openssh-client lftp rsync)
So i basically went through the whole device control system and hardened it. the planner was splitting compound goals like “open instagram and message rohit” into separate calls which broke everything. also fixed it so the loop doesn’t just bail on the first response - it actually executes the action first. scroll was crashing if the planner didn’t send a direction so now it defaults down. and exceptions in the callback handler were just silently killing the process so now everything is caught and logged properly. added loop detection so it doesn’t get stuck repeating the same thing, post-action screen verification, and 44 tests to cover it all. very happy that it worked , it took lots of time but eventually i think the results are very very good though this thing not works great on the local ai’s but with the cheap api like openrouter/free , this thing can give pretty good results
Device Control Development Update Yesterday I worked on expanding the Device Control system in my AI assistant. The idea behind this feature is to allow the AI to perform real actions on an Android device using the Accessibility Service . When the user gives a command such as “Subscribe to MrBeast on YouTube” , the main AI analyzes the request and delegates it to the Device Control tool. Current Workflow Launch the required application using: PackageManager.getLaunchIntentForPackage() startActivity() Capture a compressed screenshot of the current screen. Analyze the screenshot to identify UI elements and their screen coordinates. Navigate the interface and perform actions through the Android Accessibility APIs. Current Features Open applications Tap at (x, y) Swipe gestures Type text These core primitives allow the AI to interact with almost any Android application through UI automation. Future Improvements My main goals are to improve both speed and accuracy . Instead of navigating through multiple screens for simple system operations, I plan to add native high-level commands directly into the Device Control tool, such as: flashlight_toggle wifi_toggle bluetooth_toggle mobile_data_toggle volume_set brightness_set take_screenshot lock_screen open_notifications open_quick_settings go_home go_back open_recents These commands will allow the AI to execute common Android actions instantly without relying on visual navigation. For more complex tasks—such as interacting with third-party applications—the tool will continue using the screenshot + coordinate-based navigation pipeline. Long-Term Vision The goal is to build a hybrid Device Control system: Native commands for common Android operations (fast, reliable, and efficient). Vision-guided UI automation for complex interactions within any application. This architecture will significantly reduce execution time, improve reliability, and make the assistant capable of handling virtually any task on an Android device.
Devlog: Google Workspace Integration This week I worked on integrating Google Workspace into Zero-Assist , allowing the AI to securely access services like Gmail, Google Drive, Google Docs, and Google Sheets after the user grants permission. The ZeroClaw engine already supports Google Workspace CLI (GWS) , but it was originally built for desktop Linux and expects a desktop environment with GWS already installed. Since Zero-Assist runs inside an Alpine Linux sandbox on Android using PRoot , that approach doesn’t work directly. Instead of rewriting the integration, I kept the existing architecture and adapted it for Android. What I Implemented I modified the sandbox installation process so that GWS is installed automatically whenever the user installs the standard sandbox packages. This means users don’t need to manually install or configure the CLI. Inside the app, I added a new Google Workspace plugin under: Connections → Plugins → Installed → Google Workspace When the user signs in, the Android app completes the OAuth flow and generates the required Google Workspace configuration files. To bridge Android and the Linux sandbox, I use the existing Android ↔ PRoot bridge . The plan is: User Login ↓ Android creates GWS credentials ↓ Credentials copied into PRoot sandbox ↓ Sandbox GWS CLI uses the same credentials ↓ AI can access approved Google services This keeps authentication native while allowing the Linux CLI to work without requiring the user to touch the terminal. Google Cloud Setup I also created a dedicated Google Cloud Console project for Zero-Assist. The project uses a Web Application OAuth client , which is required by the Google Workspace CLI authentication flow. I enabled the necessary APIs, including: Gmail API Google Drive API Google Docs API Google Sheets API More APIs can be enabled as additional integrations are added. Current Problem The authentication flow itself works correctly, and users can successfully sign in. The issue is that the generated credential/configuration files are not being copied correctly into the Linux sandbox . Because of this, the sandboxed GWS CLI cannot find the required authentication files, causing every Google Workspace command to fail. The current challenge isn’t OAuth—it’s reliably synchronizing credentials between Android and the PRoot environment. Once this bridge is working, users will simply sign in once, choose which Google services they want to grant access to, and Zero-Assist will be able to securely interact with those services without any manual setup. note:This devlog is written with hands and then passed to the chatgpt to format it with the .md because im very lazy to play with those colons and #’s
Devlog here , so now i added the new cool animation (thinking orb ) this animation was totally inspired from the ( https://orbs.jakubantalik.com/ ) but the problem was that the orb was written in the typescript which wont work in our app cause our app is written in the kotlin so what i did was i downloaded the zip file from the repo pasted it to the claude and told him to convert it into kotlin for me and surprisingly the results was amazing , i will share the video recording too , and the other part i worked on was i added a few voices for my apps from the hugging face so now the user can use the custom voices too and also if he wants to use some of the default voices , the option is there do download in the app, some voices ( https://huggingface.co/rhasspy/piper-voices/resolve/main/en/en_US/lessac/medium/en_US-lessac-medium.onnx , https://huggingface.co/rhasspy/piper-voices/resolve/main/en/en_US/lessac/medium/en_US-lessac-medium.onnx , https://huggingface.co/rhasspy/piper-voices/resolve/main/en/en_GB/alan/medium/en_GB-alan-medium.onnx ) for someone whose interested …
Hello Hello Hello new devlog here , so now i started with the implementation of the MCP believe me guys once the app gets the MCP the app will go to another level , like it will then support literally any app (any app) it can perform actions like the mcp does but in simpler way also when i started with implementation i hit the problem again the code is there in the zeroclaw engine but again the problem is that its meant to run on the desktop so now we again have to do some changes in code and make the mcp run natively on the phone , i also found out some resources to do it like ( https://github.com/modelcontextprotocol/kotlin-sdk ) which is good so now the idea is something similar like shown in the screenshot below taken from the chat gpt ….
Devlog time :> so now I’m continuing with the implementation of the MCP in the app like i previously talked now when i did some tinkering with the rust code using the ai , i managed to get all the connected MCP tools into the config file of the ai the config is getting updated now but the problem is that the config is constantly keeps changing don’t know what’s happening i guess the the problem is in the toml config generator which is glitching out , so now im trying fixing it from lots of time now , i guess i might have to use the antigravity to fix this but i exhausted my weekly limit cause I’m on a free tier 😭😭.. ill catch up with yall later till then bye bye 🙆..
Update !!! new devlog here … so now after doing some more research on the mcps and the implementation plans etc etc now im finally going all on it , ive added a ui component of the MCP in the Connection/Plugin/MCP , where i added few premade mcp options like (GitHub , brave search , external postgre sql etc ..) also there i added the option of the add custom server in which use can add custom server where currently the transport options are (STDIO,HTTP,SSE,LOCALHOST_STDIO (where you can add local mcp servers using the apps like termux etc ) so now that the ui is completed now i will move on to the connection part of the ui to the backend rust engine via uniffi )
Check this out !! so yesterday i finished with the MCP implementation of the app , i implemented 4 transport method (STDIO,,HTTP,SSE and the LOCALHOST_STDIO) so when i was testing out i found out that only one of them is working properly , (the http one ) to which i connected multiple apps , mcp’s etc everything was working fine but when i tested the other transport method , not even a single one was working because it all needed the desktop to run with the specific packages so unfortunately i was not able to use it and i also find out about the nasa mcp where they daily upload the images mars rover images etc so i tried to test it but the problem was that the mcp was not http instead it was the STDIO so i was sad cause i had to fix first the mcp issue then test it but when i was in school in break i was getting board and opened the app and i had an idea like cant we just convert the normal stdio into the http mcp using the termux ? after asking to claude it said definitely we can do this so then i setuped the env(i will add a screenshot below ) and made a proxy server which converts the normal stdio mcp to the http steamtable and i was then able to access it locally using my app (i will add the image of it too) and i managed to connect to the mcp and fetch the images , now everything is working completely fine just the remaining part is the remaining transport which i will fix it some how !! also i will add some images i fetched below...
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My awesome macropad! by @aayuu4459 | Stardance
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Title: My awesome macropad! by @aayuu4459 | Starda Title: My awesome macropad! by @aayuu4459 | Stardance...
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ISS Dashboard by @zephyr94532 | Stardance
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Title: ISS Dashboard by @zephyr94532 | Stardance
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DIY lab power supply by @z0b1 | Stardance
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[{"post_id": 34696, "ts": "202 [{"post_id": 34696, "ts": "2026-07-25T16:55:31Z", "hours": 6.6042, "text": "PCB production I have redid the PCB design as for my manufacturing methods the traces and pads were to small/thin. I have now made a new version and made it successfully! BUT pin pitch on some of the components is too small(Bridge Rectifier, big capacitor etc.) mostly these oversize components, which is weird because I used KiCADs builtin footprints and theses are those models LOL, anyways I will have to tinker with that but Im just too tired for this rn. Anyways here are the images of the PCB production proccess. As always check out Crawssembly the first educational assembly language on earth! It’s made by @The_Craw"}, {"post_id": 20852, "ts": "2026-07-02T15:52:48Z", "hours": 1.6689, "text": "Redid the PCB and made code for the Arduino"}, {"post_id": 7211, "ts": "2026-06-12T01:19:42Z", "hours": 2.3086, "text": "Devlog 2 I have added the README so it contains everything needed, also organized the folders, signing out for tonight, will modify the PCB tommorow and add more info about the assembly!"}, {"post_id": 7105, "ts": "2026-06-11T21:34:40Z", "hours": 0.5425, "text": "Devlog 1 Mostly just working on the readme, finished the schematic but forgot to timelapse it so here you go a finished screenshot"}]...
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Title: DIY lab power supply by @z0b1 | Stardance
Title: DIY lab power supply by @z0b1 | Stardance
Devlogs:
Devlog 1 Mostly just working on the readme, finished the schematic but forgot to timelapse it so here you go a finished screenshot
Devlog 2 I have added the README so it contains everything needed, also organized the folders, signing out for tonight, will modify the PCB tommorow and add more info about the assembly!
Redid the PCB and made code for the Arduino
PCB production I have redid the PCB design as for my manufacturing methods the traces and pads were to small/thin. I have now made a new version and made it successfully! BUT pin pitch on some of the components is too small(Bridge Rectifier, big capacitor etc.) mostly these oversize components, which is weird because I used KiCADs builtin footprints and theses are those models LOL, anyways I will have to tinker with that but Im just too tired for this rn. Anyways here are the images of the PCB production proccess. As always check out Crawssembly the first educational assembly language on earth! It’s made by @The_Craw...
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My first slack bot! by @austinmalick9 | Stardance
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Title: My first slack bot! by @austinmalick9 | Sta Title: My first slack bot! by @austinmalick9 | Stardance...
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My first slack bot! by @aimaneon | Stardance
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Title: My first slack bot! by @aimaneon | Stardanc Title: My first slack bot! by @aimaneon | Stardance...
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My awesome macropad! by @afrinakkarabiju | Stardan My awesome macropad! by @afrinakkarabiju | Stardance...
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Title: My awesome macropad! by @afrinakkarabiju | Title: My awesome macropad! by @afrinakkarabiju | Stardance...
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My awesome macropad! by @Lucka | Stardance
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Title: My awesome macropad! by @Lucka | Stardance
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sudokun by @techmoocher | Stardance
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[{"post_id": 65773, "ts": "202 [{"post_id": 65773, "ts": "2026-09-11T04:18:21Z", "hours": 1.7275, "text": "Right now, I’m trying to implement the killer mode of sudoku!!!"}]...
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Title: sudokun by @techmoocher | Stardance
Devlog Title: sudokun by @techmoocher | Stardance
Devlogs:
Right now, I’m trying to implement the killer mode of sudoku!!!...
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Office simulator by @babybuddy | Stardance
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[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-06-05T02:51:24Z", "hours": 3.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "I made a game which allows you to hire workers to increase your gold, but you must take care of them so they dont burn out.", "repo": "https://github.com/babybuddy8/Code", "demo": "https://babybuddy8.github.io/Code/"}]...
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[{"post_id": 2546, "ts": "2026 [{"post_id": 2546, "ts": "2026-06-05T02:49:47Z", "hours": 0.9, "text": "fixed some bugs where buttons did not work"}, {"post_id": 1801, "ts": "2026-06-04T00:42:54Z", "hours": 0.9314, "text": "Completed logic and added a currency system"}, {"post_id": 1228, "ts": "2026-06-03T02:41:56Z", "hours": 0.9467, "text": "Wrote some backend logic for an office game"}]...
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Title: Office simulator by @babybuddy | Stardance
Title: Office simulator by @babybuddy | Stardance
Devlogs:
Wrote some backend logic for an office game
Completed logic and added a currency system
fixed some bugs where buttons did not work
Ships:
I made a game which allows you to hire workers to increase your gold, but you must take care of them so they dont burn out....
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Async by @Justsimone | Stardance
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[{"post_id": 2280, "ts": "2026 [{"post_id": 2280, "ts": "2026-06-04T17:55:55Z", "hours": 2.6853, "text": "Reconfigurable Controller Console - Devlog 1 This is my first devlog about my console. Just added a simple pong game to play with the console. My console is designed around the idea that you can play with your friends both by using esp-32 wifi functions and also by changing the controllers to play different games. This is my current prototype without enclosure wich will be 3d printed."}]...
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Title: Async by @Justsimone | Stardance
Devlogs:
Title: Async by @Justsimone | Stardance
Devlogs:
Reconfigurable Controller Console - Devlog 1 This is my first devlog about my console. Just added a simple pong game to play with the console. My console is designed around the idea that you can play with your friends both by using esp-32 wifi functions and also by changing the controllers to play different games. This is my current prototype without enclosure wich will be 3d printed....
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Gallery by @Hoshy | Stardance
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[{"post_id": 3435, "ts": "2026 [{"post_id": 3435, "ts": "2026-06-06T11:26:54Z", "hours": 0.295, "text": "I’m learning guys (it’s stardance’s icon !!)"}]...
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Title: Gallery by @Hoshy | Stardance
Devlogs:
I’m Title: Gallery by @Hoshy | Stardance
Devlogs:
I’m learning guys (it’s stardance’s icon !!)...
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My awesome macropad! by @akshara | Stardance
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Untitled project by @caff02 | Stardance
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Title: Untitled project by @caff02 | Stardance
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Untitled project by @trishika | Stardance
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Title: Untitled project by @trishika | Stardance
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My awesome macropad! by @klp | Stardance
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Title: My awesome macropad! by @klp | Stardance
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My first slack bot! by @En | Stardance
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Title: My first slack bot! by @En | Stardance
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My first slack bot! by @En | Stardance
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0.0
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0
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[]
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[]
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Title: My first slack bot! by @En | Stardance
|
1792810171.8805165
|
1793414971.8805165
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4663
|
Cosmofy by @mdtasdikujjaman | Stardance
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mdtasdikujjaman
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0
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0.0
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0
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[]
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[]
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Title: Cosmofy by @mdtasdikujjaman | Stardance
|
1793454977.7780435
|
1794059777.7780435
|
|
4664
|
My first slack bot! by @Rafael | Stardance
|
Rafael
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My first slack bot! by @Rafael | Stardance
|
1793433417.0663602
|
1794038217.0663602
|
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4665
|
ML-FacialTracking by @Vash | Stardance
|
Vash
|
1
|
40.22
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0
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[{"ship_num": 1, "ts": "2026-0 [{"ship_num": 1, "ts": "2026-06-22T13:36:37Z", "hours": 29.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "A custom face tracker which only points towards the trained face with a clean dashboard. It uses : cv2 os time numpy logging pathlib from collections import deque from dataclasses import dataclass from typing import Optional, Tuple", "repo": "https://github.com/Vash-Codex/Servo-Facial-Tracking", "demo": "https://github.com/Vash-Codex/Servo-Facial-Tracking/releases"}]...
|
[{"post_id": 71703, "ts": "202 [{"post_id": 71703, "ts": "2026-09-21T10:49:17Z", "hours": 0.5583, "text": "Fixed bugs and worked on the things requested for the shipment of the project"}, {"post_id": 55527, "ts": "2026-08-27T13:08:31Z", "hours": 1.2414, "text": "Now I’ll be working on the github repo and will probably rewrite my github"}, {"post_id": 50882, "ts": "2026-08-20T10:42:05Z", "hours": 7.7594, "text": "Made an Eye like UI, actually 4 eye like UI for the Basic Face detection"}, {"post_id": 49493, "ts": "2026-08-18T11:08:57Z", "hours": 1.6597, "text": "Made a change in the ui… learnt how to create a toggle as well :)"}, {"post_id": 13659, "ts": "2026-06-22T12:39:21Z", "hours": 0.7844, "text": "found a major bug in face_tracker_lbph and arduino file, fixed it but had to use codex for it 😭😭"}, {"post_id": 11266, "ts": "2026-06-18T12:57:09Z", "hours": 0.59, "text": "Updated GitHub Readme and a bit of website to fix alignment issues, Now only going to work Representation mainly"}, {"post_id": 8082, "ts": "2026-06-13T14:28:59Z", "hours": 3.8544, "text": "Did a major improvement in the LBPH file to mainly improve performance, also made lapse of wiring arduino with the servo and a really bad cover out of waste cardboard because i don’t have a 3d printer😅😅"}, {"post_id": 6800, "ts": "2026-06-11T12:23:36Z", "hours": 1.9111, "text": "Worked on Arduino File"}, {"post_id": 6685, "ts": "2026-06-11T06:15:19Z", "hours": 4.6867, "text": "Designing a case for hardware, also improved a bit of code all thanks to stackoverflow"}, {"post_id": 6084, "ts": "2026-06-10T07:17:47Z", "hours": 12.1625, "text": "improved github, did some file management and improved/fixed train lbph- training for custom facial tracking"}, {"post_id": 4706, "ts": "2026-06-08T04:02:18Z", "hours": 2.3933, "text": "Worked on the Webpage and Facial Tracking"}, {"post_id": 2595, "ts": "2026-06-05T06:26:53Z", "hours": 1.5739, "text": "Working on a webpage to represent the whole project"}, {"post_id": 2167, "ts": "2026-06-04T14:46:55Z", "hours": 0.9728, "text": "Adding a Graphical User Interface"}]...
|
Title: ML-FacialTracking by @Vash | Stardance
Dev Title: ML-FacialTracking by @Vash | Stardance
Devlogs:
Adding a Graphical User Interface
Working on a webpage to represent the whole project
Worked on the Webpage and Facial Tracking
improved github, did some file management and improved/fixed train lbph- training for custom facial tracking
Designing a case for hardware, also improved a bit of code all thanks to stackoverflow
Worked on Arduino File
Did a major improvement in the LBPH file to mainly improve performance, also made lapse of wiring arduino with the servo and a really bad cover out of waste cardboard because i don’t have a 3d printer😅😅
Updated GitHub Readme and a bit of website to fix alignment issues, Now only going to work Representation mainly
found a major bug in face_tracker_lbph and arduino file, fixed it but had to use codex for it 😭😭
Made a change in the ui… learnt how to create a toggle as well :)
Made an Eye like UI, actually 4 eye like UI for the Basic Face detection
Now I’ll be working on the github repo and will probably rewrite my github
Fixed bugs and worked on the things requested for the shipment of the project
Ships:
A custom face tracker which only points towards the trained face with a clean dashboard. It uses : cv2 os time numpy logging pathlib from collections import deque from dataclasses import dataclass from typing import Optional, Tuple...
|
1793292875.620985
|
1793379275.620985
|
|
4666
|
My first slack bot! by @Zstar | Stardance
|
Zstar
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My first slack bot! by @Zstar | Stardance
|
1793372020.0196877
|
1793976820.0196877
|
|
4668
|
My awesome macropad! by @caff02 | Stardance
|
caff02
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My awesome macropad! by @caff02 | Stardance
|
1793134132.2625744
|
1793738932.2625744
|
|
4669
|
Untitled by @ARCreator | Stardance
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ARCreator
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: Untitled by @ARCreator | Stardance
|
1792932566.391576
|
1793796566.391576
|
|
4670
|
My awesome macropad! by @tharun-11 | Stardance
|
tharun-11
|
0
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0.0
|
0
|
[]
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[]
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Title: My awesome macropad! by @tharun-11 | Starda Title: My awesome macropad! by @tharun-11 | Stardance...
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1793476443.2828548
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1794081243.2828548
|
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4671
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Small ChromeBrowser by @jacob6855 | Stardance
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jacob6855
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0
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0.0
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0
|
[]
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[]
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Title: Small ChromeBrowser by @jacob6855 | Stardan Title: Small ChromeBrowser by @jacob6855 | Stardance...
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1793458563.8040068
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1794063363.8040068
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4672
|
My awesome macropad! by @Aiman | Stardance
|
Aiman
|
0
|
0.0
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0
|
[]
|
[]
|
Title: My awesome macropad! by @Aiman | Stardance
|
1793368239.5832407
|
1793973039.5832407
|
|
4673
|
Streaky by @Karthik2 | Stardance
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Karthik2
|
0
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0.0
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0
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[]
|
[]
|
Title: Streaky by @Karthik2 | Stardance
|
1793382564.606755
|
1793987364.606755
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|
4674
|
Untitled by @ishowspeed | Stardance
|
ishowspeed
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0
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0.0
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0
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[]
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[]
|
Title: Untitled by @ishowspeed | Stardance
|
1792954171.8491209
|
1793818171.8491209
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|
4675
|
My first slack bot! by @zazzie | Stardance
|
zazzie
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My first slack bot! by @zazzie | Stardance
|
1792954089.662272
|
1793818089.662272
|
|
4676
|
Record Player clock by @JasonC9 | Stardance
|
JasonC9
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0
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0.0
|
0
|
[]
|
[]
|
Title: Record Player clock by @JasonC9 | Stardance
|
1792947187.0030398
|
1793811187.0030398
|
|
4677
|
AutoPot by @OriVersal | Stardance
|
OriVersal
|
1
|
0.0
|
0
|
[{"ship_num": 1, "ts": "2026-1 [{"ship_num": 1, "ts": "2026-10-20T13:19:56Z", "hours": 0.0, "multiplier": null, "payout": 0, "blessing": "neutral", "text": "I finally finished the project!!! The project was about a pot that has all the features of other smart planters. In other words, the ultimate smart planter. It does everything from watering the plant to giving it sunshine with the option for automatic use as well. The remote access is also pretty neat. I’d say the most difficult part of the project was me. I was procrastinating a lot and couldn’t keep up consistent progress. Eventually, I locked in and went all out. I am super proud of the project and I can definitely say that every part and thing about it makes me proud. If you were to test it or build it yourself the thing you would prolly have to know is that the space inside the component cabinet is pretty small, so the parts are basically air tight. I am thankful for this opportunity. The end", "repo": "https://github.com/Oriprogram/AutoPot", "demo": ""}]...
|
[{"post_id": 75472, "ts": "202 [{"post_id": 75472, "ts": "2026-09-30T05:51:51Z", "hours": 1.5089, "text": "Just workin Basically I am almost finisheddd yayy"}, {"post_id": 67344, "ts": "2026-09-13T12:48:01Z", "hours": 7.9831, "text": "So as you might of guessed, this is a collection of multiple days. Man I am kinda losing motivation to do my project. It feels bland and boring to do. I am almost done finishing it. The only thing left is the software part. Idk how I am going to do the 3d printing part since its super expensive and my financial situation wont allow that much money spending. The circuit is done 100% and my 3d model is done. I believe I could ship it but I wouldnt have a working model to showcase but in theory everything works correctly. Anyways yeah."}, {"post_id": 65140, "ts": "2026-09-10T02:19:05Z", "hours": 8.2356, "text": "So this is another collection of multiple days I didnt know creating 3D CAD models would be this difficult. First I had to learn how to do this and then I had to actually model it myself. Along the way there were several things I encountered that I added that arent in the sketch: I added holes for air circulation in the place where water is taken from the tray since I realized that there needs to be air for water to effectively be removed from the dirt. I made the component compartment a bit shorter and the plant compartment taller for plant height since it need a good height for healthy roots. I added the holes and the pipe for the plastic flexible pipe. I added the tray for water storage and I think it turned out pretty good. Of course I also had to do the model it self but yk. Because of my slow laptop doing anything was HELL."}, {"post_id": 60728, "ts": "2026-09-03T09:10:33Z", "hours": 8.0167, "text": "Helloooo So this is a collection of multiple days of work since I was too lazy to publish them. Since I hit almost 10 hours I decided to post this. In these couple of project days I was able to do a lot of stuff that I wanted to do!!! I fully integrated my project onto Obsidian. And let me tell you, Obsidian is the Goat. It is so easy to use and so comfortable. I was able to get the sketch done on it and I was also able to put all the components that I needed to but onto it as well!! Additionally the whiteboard and canvas feature really helped me. Using these features I mapped out the circuit of my project! I chose all the components that I needed and bought everything that I needed. In total it cost me around ~2000 kgrz som which is about 25 dollars. By the time the components arrive, I started the app. I am not good with building apps so I had to vibe code it. I am pretty proud with the design that I chose so its pretty good. However it still needs further testing. I was able to draw the icon for the app and the face expressions for the pot itself. There were multiple issues that I faced while doing this tho. My first issue stems from the water source. My trivia was how I was going to get the water: combine it with the pot and make it sleek or make it a separate printable water bottle you can place on the ground? At the end I chose to do the water bottle method since this will allow me to store more water for future use and it will be less of a pain to print. My second issue came when I was choosing which LED strip to buy. I was stuck between the purple ones and the COD ones. Although both are similar I did not like the Purple color that was radiating from the Purple strips. Because of that I just chose to do the COD ones."}, {"post_id": 35849, "ts": "2026-07-27T15:38:40Z", "hours": 1.0833, "text": "Day #5 Ok day 5 was a pretty short day however I was able to connect the circuit that I had in the wowki website to my blynk “app”. So my first problem came when I was trying to open the blynk website. I came to realize that blynk wouldnt open in my country so I just used a vpn and it worked perfectly right (in the first attempt) so yeah. After that I was able to open a project and then some datastreams for my values and then I copied the 3 lines of code for connecting with my project. After that I went and downloaded the blynk app itself and created a very simple UI for the project. There I also had to assign the datastreams to like gauges or buttons like you can see in the screenshot. After that I searched up how I can translate values from the ESP32 into the blynk app and it was pretty simple. You just had to use VirtualWrite and some other stuff. At the end I was able to a very simple app test and data test. In the future sessions I hope to add more features."}, {"post_id": 33546, "ts": "2026-07-23T16:11:13Z", "hours": 2.3336, "text": "Day #3-4 These days were quite the progressive ones. I had a lot of trouble trying to understand how I could simulate the circuitry of my project accurate enough. First I was thinking of using TinkerCard. It was pretty useful. I was able to use it to learn and practice circuitry using arduino. But it was very limiting and didnt have the components I was looking for (ESP32) While in my search I was able to find wokwi. Wokwi is incredible, let me tell you that. There I just could do everything. There wasnt all the components I needed but I was able to find a replacement for them (temporary). At the end I had a: Relay modul (for the water pump) Relay modul (for the LED lights) ILI9341 2.8” screen (for the screen) Potentio meter (as a replacement for soil moisture sensor) Potentio meter (as another replacement for soil PH sensor) DHT22 (for air quality) BreadBoard (will be replaced later) ESP32 S3 (prolly use another version of the ESP32 but I will use it for now.) Thankfully I was able to kinda have a demo at the end as well. These two sessions had a lot more success than I thought it would. I thought I would just be spending time learning, but I was able to create a demo."}, {"post_id": 16837, "ts": "2026-06-27T10:26:17Z", "hours": 1.1667, "text": "Day #2. So today I just messed around with what components I would be using for my pot. Since I lack severe knowledge required for the pot I just did what I could and used what knowledge I had. Of course most of the components that I did choose are placeholders. I mean if they work I will prolly keep em. So here are the components that I have currently chosen: An LED flourescent light that helps the plant photosynthesize. DTH22 Temperature sensor Capacitive dirt moisture sensor Moisture sensor A 6V DC water pump ESP32 chip MP1584 resistor 12V 2 channel Relay Module MAX485 Module Temporary: jumper wire + breadboard. So these are all the components that I currently think I will need. I will try and learn how to actually wire these in tomorrows session most likely? And I will prolly use some simulators for it too. And thats all for today."}, {"post_id": 15720, "ts": "2026-06-25T16:02:14Z", "hours": 1.5003, "text": "Day #1. So today was the day I created the idea for the pot. I had the idea of an AutoPot before but I didnt really have a vivid picture of it, so yeah. Today I mapped out an example sketch of it. At first I was anxious. I thought that my idea was too overpopulated, there were like a lot of ideas earily similar to mine. So I started to become less motivated. But then, I started noticing a pattern. Not a single one of the pots had all the features and ideas of MY version of the AutoPan. So I started to note down all the features of my Pot and add features that I didnt have. So collectively I had the ultimate autopot. Here are all the features. Features: Comes in 3 different sizes (you have 3 different sized models) An LED flourescent light that helps the plant photosynthesize. Sensors to sense the temperature, moisture, quality of the dirt. A pump for watering preferrably from an external source. An app connected to your Wi-Fi, in which you can choose what plant is inside of the pot and based on your choice the app will recommend and adject its features (LED, Water), or give you a recommendation (swap out dirt or too hot). Maybe be a screen for the Plant (optional idk for now, because it might increase price too much)"}]...
|
Title: AutoPot by @OriVersal | Stardance
Devlogs: Title: AutoPot by @OriVersal | Stardance
Devlogs:
Day #1. So today was the day I created the idea for the pot. I had the idea of an AutoPot before but I didnt really have a vivid picture of it, so yeah. Today I mapped out an example sketch of it. At first I was anxious. I thought that my idea was too overpopulated, there were like a lot of ideas earily similar to mine. So I started to become less motivated. But then, I started noticing a pattern. Not a single one of the pots had all the features and ideas of MY version of the AutoPan. So I started to note down all the features of my Pot and add features that I didnt have. So collectively I had the ultimate autopot. Here are all the features. Features: Comes in 3 different sizes (you have 3 different sized models) An LED flourescent light that helps the plant photosynthesize. Sensors to sense the temperature, moisture, quality of the dirt. A pump for watering preferrably from an external source. An app connected to your Wi-Fi, in which you can choose what plant is inside of the pot and based on your choice the app will recommend and adject its features (LED, Water), or give you a recommendation (swap out dirt or too hot). Maybe be a screen for the Plant (optional idk for now, because it might increase price too much)
Day #2. So today I just messed around with what components I would be using for my pot. Since I lack severe knowledge required for the pot I just did what I could and used what knowledge I had. Of course most of the components that I did choose are placeholders. I mean if they work I will prolly keep em. So here are the components that I have currently chosen: An LED flourescent light that helps the plant photosynthesize. DTH22 Temperature sensor Capacitive dirt moisture sensor Moisture sensor A 6V DC water pump ESP32 chip MP1584 resistor 12V 2 channel Relay Module MAX485 Module Temporary: jumper wire + breadboard. So these are all the components that I currently think I will need. I will try and learn how to actually wire these in tomorrows session most likely? And I will prolly use some simulators for it too. And thats all for today.
Day #3-4 These days were quite the progressive ones. I had a lot of trouble trying to understand how I could simulate the circuitry of my project accurate enough. First I was thinking of using TinkerCard. It was pretty useful. I was able to use it to learn and practice circuitry using arduino. But it was very limiting and didnt have the components I was looking for (ESP32) While in my search I was able to find wokwi. Wokwi is incredible, let me tell you that. There I just could do everything. There wasnt all the components I needed but I was able to find a replacement for them (temporary). At the end I had a: Relay modul (for the water pump) Relay modul (for the LED lights) ILI9341 2.8” screen (for the screen) Potentio meter (as a replacement for soil moisture sensor) Potentio meter (as another replacement for soil PH sensor) DHT22 (for air quality) BreadBoard (will be replaced later) ESP32 S3 (prolly use another version of the ESP32 but I will use it for now.) Thankfully I was able to kinda have a demo at the end as well. These two sessions had a lot more success than I thought it would. I thought I would just be spending time learning, but I was able to create a demo.
Day #5 Ok day 5 was a pretty short day however I was able to connect the circuit that I had in the wowki website to my blynk “app”. So my first problem came when I was trying to open the blynk website. I came to realize that blynk wouldnt open in my country so I just used a vpn and it worked perfectly right (in the first attempt) so yeah. After that I was able to open a project and then some datastreams for my values and then I copied the 3 lines of code for connecting with my project. After that I went and downloaded the blynk app itself and created a very simple UI for the project. There I also had to assign the datastreams to like gauges or buttons like you can see in the screenshot. After that I searched up how I can translate values from the ESP32 into the blynk app and it was pretty simple. You just had to use VirtualWrite and some other stuff. At the end I was able to a very simple app test and data test. In the future sessions I hope to add more features.
Helloooo So this is a collection of multiple days of work since I was too lazy to publish them. Since I hit almost 10 hours I decided to post this. In these couple of project days I was able to do a lot of stuff that I wanted to do!!! I fully integrated my project onto Obsidian. And let me tell you, Obsidian is the Goat. It is so easy to use and so comfortable. I was able to get the sketch done on it and I was also able to put all the components that I needed to but onto it as well!! Additionally the whiteboard and canvas feature really helped me. Using these features I mapped out the circuit of my project! I chose all the components that I needed and bought everything that I needed. In total it cost me around ~2000 kgrz som which is about 25 dollars. By the time the components arrive, I started the app. I am not good with building apps so I had to vibe code it. I am pretty proud with the design that I chose so its pretty good. However it still needs further testing. I was able to draw the icon for the app and the face expressions for the pot itself. There were multiple issues that I faced while doing this tho. My first issue stems from the water source. My trivia was how I was going to get the water: combine it with the pot and make it sleek or make it a separate printable water bottle you can place on the ground? At the end I chose to do the water bottle method since this will allow me to store more water for future use and it will be less of a pain to print. My second issue came when I was choosing which LED strip to buy. I was stuck between the purple ones and the COD ones. Although both are similar I did not like the Purple color that was radiating from the Purple strips. Because of that I just chose to do the COD ones.
So this is another collection of multiple days I didnt know creating 3D CAD models would be this difficult. First I had to learn how to do this and then I had to actually model it myself. Along the way there were several things I encountered that I added that arent in the sketch: I added holes for air circulation in the place where water is taken from the tray since I realized that there needs to be air for water to effectively be removed from the dirt. I made the component compartment a bit shorter and the plant compartment taller for plant height since it need a good height for healthy roots. I added the holes and the pipe for the plastic flexible pipe. I added the tray for water storage and I think it turned out pretty good. Of course I also had to do the model it self but yk. Because of my slow laptop doing anything was HELL.
So as you might of guessed, this is a collection of multiple days. Man I am kinda losing motivation to do my project. It feels bland and boring to do. I am almost done finishing it. The only thing left is the software part. Idk how I am going to do the 3d printing part since its super expensive and my financial situation wont allow that much money spending. The circuit is done 100% and my 3d model is done. I believe I could ship it but I wouldnt have a working model to showcase but in theory everything works correctly. Anyways yeah.
Just workin Basically I am almost finisheddd yayy
Ships:
I finally finished the project!!! The project was about a pot that has all the features of other smart planters. In other words, the ultimate smart planter. It does everything from watering the plant to giving it sunshine with the option for automatic use as well. The remote access is also pretty neat. I’d say the most difficult part of the project was me. I was procrastinating a lot and couldn’t keep up consistent progress. Eventually, I locked in and went all out. I am super proud of the project and I can definitely say that every part and thing about it makes me proud. If you were to test it or build it yourself the thing you would prolly have to know is that the space inside the component cabinet is pretty small, so the parts are basically air tight. I am thankful for this opportunity. The end...
|
1793404055.3737428
|
1793490455.3737428
|
|
4678
|
MLA Text Editor by @hacker-fox | Stardance
|
hacker-fox
|
0
|
16.45
|
0
|
[]
|
[{"post_id": 36814, "ts": "202 [{"post_id": 36814, "ts": "2026-07-29T03:14:29Z", "hours": 1.3458, "text": "I have spent some time consolidating code in areas such as the Modal. This will make it more consistent to close the modal using esc and clicking outside. This will make it cleaner to use my app. This modals use daisyUI, but eventually I plan to move off of daisyUI for better accessibility support. I have also dramatically improved the usability of new citation feature."}, {"post_id": 35221, "ts": "2026-07-26T14:52:55Z", "hours": 1.3419, "text": "I have added a new inline citation option, this will make it easier for people to add citations while they are working on their document. In the future, I want to clean up this citation maker screen since it is messy at the moment."}, {"post_id": 34277, "ts": "2026-07-24T20:56:05Z", "hours": 6.1714, "text": "I have added citations, one of the most difficult aspects of the MLA format to my app. Eventually, I would like to add a quick access to citations using a hotkey such as @ or / like Notion or Google Docs for easiest adding. I used AI to help configure these menus. There is sometimes confusing rules for MLA, and I used it to help speed up this process. In the future, I will help clean up this menu."}, {"post_id": 23234, "ts": "2026-07-06T01:47:33Z", "hours": 7.5911, "text": "I am working on a block-based text editor that makes it simple to maintain MLA format. In school, many teachers require the MLA format in any submission. This format can be difficult to maintain, and it can be useful to work in an app that forces you to follow MLA’s requirements. So far, I have built the UI and set up the storing system. I have run into difficulties with setting up the sidebar. When originally making it, both were taking up the entire space, creating nasty double-scrolling. Most of this app is based off of my previous Bubblesheets web project that I had made before."}]...
|
Title: MLA Text Editor by @hacker-fox | Stardance
Title: MLA Text Editor by @hacker-fox | Stardance
Devlogs:
I am working on a block-based text editor that makes it simple to maintain MLA format. In school, many teachers require the MLA format in any submission. This format can be difficult to maintain, and it can be useful to work in an app that forces you to follow MLA’s requirements. So far, I have built the UI and set up the storing system. I have run into difficulties with setting up the sidebar. When originally making it, both were taking up the entire space, creating nasty double-scrolling. Most of this app is based off of my previous Bubblesheets web project that I had made before.
I have added citations, one of the most difficult aspects of the MLA format to my app. Eventually, I would like to add a quick access to citations using a hotkey such as @ or / like Notion or Google Docs for easiest adding. I used AI to help configure these menus. There is sometimes confusing rules for MLA, and I used it to help speed up this process. In the future, I will help clean up this menu.
I have added a new inline citation option, this will make it easier for people to add citations while they are working on their document. In the future, I want to clean up this citation maker screen since it is messy at the moment.
I have spent some time consolidating code in areas such as the Modal. This will make it more consistent to close the modal using esc and clicking outside. This will make it cleaner to use my app. This modals use daisyUI, but eventually I plan to move off of daisyUI for better accessibility support. I have also dramatically improved the usability of new citation feature....
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1793425799.9786642
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1794030599.9786642
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4679
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Untitled by @blueberry142387 | Stardance
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blueberry142387
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0
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0.0
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0
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[]
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[]
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Title: Untitled by @blueberry142387 | Stardance
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1793429256.094128
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1794034056.094128
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4680
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My first slack bot! by @blueberry142387 | Stardanc My first slack bot! by @blueberry142387 | Stardance...
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blueberry142387
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0
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0.0
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0
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[]
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[]
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Title: My first slack bot! by @blueberry142387 | S Title: My first slack bot! by @blueberry142387 | Stardance...
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1793389819.9956362
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1793994619.9956362
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4681
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revision site by @Zstar | Stardance
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Zstar
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0
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4.81
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0
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[]
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[{"post_id": 5488, "ts": "2026 [{"post_id": 5488, "ts": "2026-06-09T09:18:04Z", "hours": 2.6861, "text": "I added flashcards and a little multiple choice quiz in which was a little hard to learn how to code but it’s made the website look way better and also much more interactive I’m also gonna add in some sections to write answers for exam questions. I really want to make it as interactive as possible because the more interactive it is the better it is for revision"}, {"post_id": 2028, "ts": "2026-06-04T09:46:58Z", "hours": 0.6006, "text": "ok ok so it hit me that my code ain’t pretty so i consumed some more videos and got to editing and now its looking way better but i am starting to regret choosing this project I mean their are a lot of notes i have to put in so i might only do the most basic biology notes idk but I’m learning a lot so 😃Anyway here is what it looks like so far on the Html viewer"}, {"post_id": 1456, "ts": "2026-06-03T14:39:54Z", "hours": 1.1422, "text": "Sooo I’ve learnt a lot I spent a while watching videos to figure out how to do the basics and i feel like I now understand how rlly basic coding works. I found a html viewer to track my progress so here’s what it looks like so far. I added some notes just on what parts of the cells do and I’m going to use making it as some revision for bio and maybe it’ll be a resource that other students can use when I eventually publish it."}, {"post_id": 924, "ts": "2026-06-02T17:47:01Z", "hours": 0.3847, "text": "I’m building a revision website to learn basic html and css"}]...
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Title: revision site by @Zstar | Stardance
Devlog Title: revision site by @Zstar | Stardance
Devlogs:
I’m building a revision website to learn basic html and css
Sooo I’ve learnt a lot I spent a while watching videos to figure out how to do the basics and i feel like I now understand how rlly basic coding works. I found a html viewer to track my progress so here’s what it looks like so far. I added some notes just on what parts of the cells do and I’m going to use making it as some revision for bio and maybe it’ll be a resource that other students can use when I eventually publish it.
ok ok so it hit me that my code ain’t pretty so i consumed some more videos and got to editing and now its looking way better but i am starting to regret choosing this project I mean their are a lot of notes i have to put in so i might only do the most basic biology notes idk but I’m learning a lot so 😃Anyway here is what it looks like so far on the Html viewer
I added flashcards and a little multiple choice quiz in which was a little hard to learn how to code but it’s made the website look way better and also much more interactive I’m also gonna add in some sections to write answers for exam questions. I really want to make it as interactive as possible because the more interactive it is the better it is for revision...
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1793163095.534246
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1793767895.534246
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4682
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MARS WEBSITE by @Henrique | Stardance
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Henrique
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0
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1.03
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0
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[]
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[{"post_id": 2860, "ts": "2026 [{"post_id": 2860, "ts": "2026-06-05T18:36:39Z", "hours": 1.0275, "text": "devlog 1 Hi ! My name is Henrique and I am from Brazil. I am working on a Mars website. This website is based on Spacex Mars website. I am almost done, i still have to find a way to trasform my html and js files into a website *with a domain Any suggests?"}]...
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Title: MARS WEBSITE by @Henrique | Stardance
Devl Title: MARS WEBSITE by @Henrique | Stardance
Devlogs:
devlog 1 Hi ! My name is Henrique and I am from Brazil. I am working on a Mars website. This website is based on Spacex Mars website. I am almost done, i still have to find a way to trasform my html and js files into a website *with a domain Any suggests?...
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1793404403.0121312
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1794009203.0121312
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4683
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Roguelike Car Chase Game by @Caleb | Stardance
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Caleb
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0
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0.0
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0
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[]
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[]
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Title: Roguelike Car Chase Game by @Caleb | Starda Title: Roguelike Car Chase Game by @Caleb | Stardance...
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1793472945.7878144
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1794077745.7878144
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