δΈδΊΊ = δΈζ―εΌεε’ι — One person, a full AI development team
Overview
Agent Swarm is a framework for running an autonomous AI development team. It connects 4 modules β daily issue scanning, task tracking, AI code review, and intelligent failure recovery β into a self-sustaining loop. You set the direction; the agents handle the rest.
Modules
Four purpose-built modules that snap together into a fully autonomous development pipeline.
Runs daily at 09:00 EST via cron. Scans GitHub Issues for new actionable items, filters already-handled tasks, and automatically dispatches them to the coding agent β all before you've had your first coffee.
Every spawned agent writes to active-tasks.json on creation and
updates it on completion. One command gives you real-time status across every
parallel task, PR URL, and outcome note.
Every PR triggers a self-hosted GitHub Actions runner on the Mac mini. It pipes the diff through Gemini CLI for a full code review covering bugs, performance, security, and quality β then posts the verdict as a PR comment and fires an iMessage notification.
Intelligent failure recovery that never blindly retries. When an agent fails, it classifies the failure into one of 4 types β missing context, direction drift, environment issue, or task too large β then rewrites the prompt accordingly before spawning again.
Architecture
A closed-loop orchestration pipeline. The main agent dispatches work; everything else runs autonomously β right up to the iMessage notification in your pocket.
You β Main Agent
Set a direction or let Morning Scan surface tasks automatically from GitHub Issues.
Main Agent β Coding Agent
The orchestrator spawns a dedicated coding agent (tmux + Claude Code) and registers the task in active-tasks.json.
Coding Agent β GitHub PR
The coding agent implements the feature or fix and opens a pull request β no human intervention.
PR β Gemini AI Review
GitHub Actions triggers the self-hosted runner on the Mac mini. Gemini reviews the diff and posts a verdict comment.
Review β iMessage Notification
Once the review completes, a notification fires to your phone. APPROVE, REQUEST_CHANGES, or COMMENT β you're always in the loop.
Failure β Ralph Loop V2
If any step fails, the failure is classified (A/B/C/D), the prompt is rewritten, and the agent is re-spawned intelligently.
Ralph Loop V2 β Failure Types
Missing Context
File not found, incomplete output, "can't see the full picture"
Direction Drift
Agent did X but you wanted Y, ignored constraints
Environment Issue
Command errors, missing deps, permission failures
Task Too Large
Timeout, chaotic output, stuck midway β needs splitting
Coverage
Every step of the development loop β from triage to shipping β handled by agents so you can stay in the architect's seat.
Morning Scan scans GitHub Issues daily and auto-routes actionable items to the coding agent.
A dedicated coding agent (tmux + Claude Code) implements every task autonomously end-to-end.
Gemini AI reviews every pull request via a self-hosted GitHub Actions runner on the Mac mini.
Ralph Loop V2 classifies failures into 4 types and rewrites the prompt before retrying.
active-tasks.json registers every spawned agent β status, PR URL, and notes in one place.
iMessage alerts fire when PR review completes, so nothing slips through without your awareness.
Coming Soon
Be the first to know when this plugin launches.