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archwhere tapaskar/archwhere

Mission control for AI coding agents: every PR on the architecture map, an MCP server, a tamper-evident record of who decided what, and which branches in flight will collide.

https://www.npmjs.com/package/archwhere β†—
HEALTH ? 92 / Healthy
// hidden gem// release machine agentic-aiai-agentsarchitecturearchitecture-as-codeclaudegithub-actionsmermaidaudit-logc4-modelcode-review ?

// readme

archwhere

Your AI coding agents ship thirty PRs a week. Do you know where they land?

archwhere puts every change β€” every PR, every task, every agent β€” on a declared architecture map: which component it touches, whether that component is a security zone, and what needs you right now. Then it goes further: the map becomes the place you talk to your agents.

Mission control on a fictional product: the attention rail (security β†’ blocked β†’ needs-attention β†’ ready-to-merge), the component map with live badges, and a thread pinned to a component β€” answered by a coding agent, with its PR.

Zero dependencies. One JSON file. Works with Claude, or any agent that can see GitHub.

Why

Supervising an agent workforce diff-by-diff doesn’t scale. Architecture tools (Structurizr, IcePanel) assume a human architect maintains the model β€” so the model rots. CODEOWNERS and labelers map files to owners but carry no meaning.

archwhere inverts it: your agents maintain the map as a condition of merging (there’s a SKILL.md that tells them how, and archwhere check fails CI when the map goes stale). You read components, not diffs.

Quickstart

npx archwhere init
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