Multi-Agent Development Pipeline for OpenClaw
Give it a task. Get back a tested, reviewed PR.
Six AI agents handle the rest.
From a plain-language task description to a fully tested, reviewed pull request — autonomously.
Each agent has a focused role, its own system prompt, and clear handoff boundaries.
Decomposes tasks into ordered user stories with acceptance criteria, dependencies, and estimated complexity.
Creates the feature branch, runs initial builds, and establishes the test baseline before development begins.
Implements one user story per session with production code and tests. Loops until all stories are complete.
Checks each story against its acceptance criteria. Runs tests, verifies build, retries on failure.
Runs integration and end-to-end tests across the full feature. Catches cross-story regressions.
Reviews the final pull request for code quality, security, and completeness. Approves or requests changes.
Production-grade patterns that make autonomous development actually work.
Tasks are broken into discrete user stories with clear acceptance criteria. Each story is implemented, tested, and verified independently.
When tests fail or criteria aren't met, the pipeline retries automatically. Stories loop between Developer and Verifier until they pass.
A watchdog process monitors pipeline health and recovers from stuck states, crashed agents, and stalled builds.
Pipeline state is saved to disk after every step. Sessions can crash and resume without losing completed work.
Pre-commit hooks block credentials, API keys, and secrets from ever reaching the repository. Baked in, not bolted on.
Agents poll for work on offset schedules to avoid contention and respect API rate limits across parallel pipelines.
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