MostAshraf/ai-sdlc-harness
14 stars · Last commit 2026-08-15
Governed multi-agent SDLC pipeline for Claude Code and Qwen Code — plan → adversarial plan review → proven-red TDD → security scan → PR, with tamper-evident evidence at every step. Azure DevOps, Jira, GitHub, GitLab, Zoho, and local-markdown providers. Language-agnostic, discovery-driven.
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# ai-sdlc-harness [](https://github.com/MostAshraf/ai-sdlc-harness/actions/workflows/ci.yml) [](https://github.com/MostAshraf/ai-sdlc-harness/releases/latest) [](LICENSE) [](#claude-code) [](#qwen-code) [](https://codeguilds.dev/packages/ai-sdlc-harness) **A governed multi-agent SDLC pipeline for Claude Code and Qwen Code** — a ground-up rewrite of [ai-sdlc-harness](https://github.com/MostAshraf/ai-sdlc-harness). Drives a real engineering workflow — fetch → scope-confirmed plan → independent plan review → proven-red TDD → review → security → PR → comment rounds → reconcile → metrics — across one or many repos. No application code lives here: only the pipeline manifest, the Python core that enforces it, and the agents, skills, and hooks that run it. | Command | Purpose | |---|---| | `/init-workspace` | One-time setup interview: provider, repos, discovered toolchain, verification gate | | `/dev-workflow <work-item-id>` | Take a work item from requirements to merged PR end-to-end | | `/story-workflow <command> <work-item-id>` | Shape a story's quality before it's built: `analyze` · `refine` · `improve` · `groom` | | `/workflow-status` | Read-only dashboard: cursor, tasks, gates, flagged events, run-health verdict per run | | `/workspace-config` | Change one config section without re-running the interview | | `/add-repo` | Register one new repo into an already-bootstrapped workspace | | `/migrate-workspace` | Adopt a v2.x workspace: config carries over, run history stays archived in place |