agent-debugger is an early open-source MVP for turning repeated backend troubleshooting habits into executable runbooks for AI agents.
Repository: debug-runbook
This release focuses on one narrow but reusable layer:
- runbook selection
- ordered evidence collection
- evidence normalization
- evidence-based conclusion generation
- MCP-based integration surface
It does not ship the original internal production DAG, permission system, or repair workflows that inspired the project.
Many online incidents are investigated with a repeatable sequence:
- compare actual behavior with the expected result
- inspect cache
- inspect persistence
- inspect trace / execution flow
- decide which evidence-backed conclusion is most likely
This repository packages that style of investigation into a replayable, inspectable framework.
- zero-config replay demo
- benchmark over built-in fixture cases
- metadata consistency checks
- built-in runbooks for:
- missing expected side effects
- stale cache views
- abnormal persisted state
- custom runbook loading through config
- read-only adapter model for Langfuse, Postgres, and Redis
Built-in runbooks intentionally cover a limited set of locator types:
request_not_effective:request_id,order_idcache_stale:order_id,task_idstate_abnormal:order_id,task_id
Broader locator support should be added through custom runbooks or later releases.
- rewrote the README around a real incident pattern and a zero-config demo path
- reduced installation friction by adding
pnpm demo - fixed config interpolation so unresolved env vars are preserved safely
- made
runbooks:config entries work at runtime for custom runbooks - tightened package boundaries with
engines,files, andprepack - documented MVP boundaries more explicitly
pnpm test -- --run
pnpm build
pnpm demo
pnpm benchmark
pnpm check
npm pack --dry-run- built-in runbooks are intentionally narrow
- benchmark results validate replay cases, not every real integration path
- no write-path or repair automation is shipped in this repository
- real production observability and orchestration setup must be provided by the user
Use wording like:
- early open-source MVP
- research preview
- replayable incident investigation framework
Avoid wording like:
- production-ready self-healing platform
- general autonomous debugging engine
- safe automatic repair system