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asfsdsf / multi_agents_sample

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A personal multi agent sample to find WebUI bugs

19
0
69% credibility
Found Mar 11, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Shell
AI Summary

A sample set of collaborative AI agents that find, verify, repair, and learn from bugs in web user interfaces.

How It Works

1
🔍 Discover bug-fixing helpers

You find a handy set of smart assistants that team up to spot and fix glitches in your web app's look and feel.

2
📁 Add helpers to your project

You copy the helpers folder right into the main spot of your own web app project.

3
✏️ Customize for your app

You update a few notes to tell the helpers about your web app's web address and special spots to check.

4
🚀 Start your web app

You turn on your web app so the helpers can visit and explore it like a real user.

5
🤖 Launch the bug hunt

You give the command to start the team—they automatically search for issues, check them, suggest fixes, and even improve your code.

6
📊 Review the reports

You read simple reports on what bugs they found, why they matter, and how they patched them up.

✅ Bugs gone, app better

Your web app runs smoother with fresh fixes committed, and tips to prevent future glitches.

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AI-Generated Review

What is multi_agents_sample?

This Shell-based workflow deploys a squad of AI agents—Finder, Identifier, Fixer, and Reflector—to hunt, diagnose, patch, and learn from bugs in local WebUIs running on port 15373. Drop the scripts into your personal GitHub repository root, tweak prompts for your app's URLs and tests, and run manual commands like `./multi_agents/start_agent finder "check login flow"` or `./multi_agents/auto_agents "fix dashboard glitches"` for endless loops powered by Codex CLI, tmux sessions, Playwright browsers, and DeepSeek API. It solves the drudgery of manual WebUI debugging by chaining agents via timestamped reports in a shared bugs folder, outputting git commits and detailed Markdown case files.

Why is it gaining traction?

Unlike solo AI tools or basic e2e tests, it orchestrates a full bug lifecycle with file handoffs that prevent duplicates and enable pausing/resuming, all in headed browsers you can watch. Developers dig the auto mode that iterates finder-to-fixer without babysitting, integrating seamlessly with personal GitHub accounts for branching fixes via personal GitHub tokens. Low Stars (19) but hooks tinkerers with Codex who want agent swarms over one-shot prompts.

Who should use this?

Backend devs building WebUIs who already run Codex and tmux on MacOS/Linux, especially those debugging integration tests in personal GitHub repos for work. Frontend teams tired of flakey Playwright scripts will like the visible browser probes and auto-generated verification tests. Skip if you're on Windows or lack DeepSeek keys for automation.

Verdict

Niche but clever for Codex users—grab it for personal multi-agent experiments in your personal GitHub Copilot setup, despite 0.7% credibility score and low maturity from 19 stars. Solid docs make setup fast, but expect prompt tweaks for production; test on a throwaway personal GitHub page first.

(198 words)

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