Review a work session to identify slow steps, failures, missing information, and useful patterns. Then make concise, evidence-based updates to relevant documentation so confirmed lessons can help with future sessions.
End-of-session reflection. Reviews friction encountered during the session and proposes updates to docs/ to capture lessons learned.
Run score Not tested
See how to installReview the instructions the agent will receive before you install.
Reflect on the current session and update documentation with lessons learned.
Identify friction: Review what happened in this session:
git diff main...HEAD --stat to see what files were touchedRead current docs: Read the docs that were relevant to this session:
docs/validation.mddocs/enterprise.mdPropose updates: For each piece of friction, decide if it warrants a doc update:
Apply updates: Edit the relevant docs/ files. Keep changes minimal and specific — add only what would have saved time this session.
Report: Summarize what was added/changed and why.
docs/ and add a pointer in CLAUDE.mdNo reviews yet. Tell others what you thought.
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Plan the code changes needed to add a TriggerCrud-based trigger to Windmill. The checklist covers backend, database, API, CLI, frontend, capture, and validation work so the new trigger can be managed across the product.
Improve Windmill’s AI chat by reviewing its tools, prompts, result shapes, and context usage. The guidance helps place shared instructions where chat and CLI can use them, reduce repeated token costs, and compare behavior before and after changes with A/B evaluations.
Create and run black-box benchmarks for Windmill AI generation modes such as flows, apps, scripts, CLI, and global requests. Each case exercises the production path, checks hard requirements, and uses an LLM judge to assess user-facing behavior before and after changes.
Use this reference to work with Windmill resources from the command line, including scripts, flows, datatables, and workspace settings. It also covers listing jobs, inspecting details and logs, retrieving results, and rerunning or restarting executions when investigating failures.
Use this skill to shape modules with small interfaces and substantial behavior behind them. It helps you decide where a seam belongs, reduce complexity exposed to callers, and make code easier to test and maintain.
Use this skill to review pending changes, select only the relevant files for staging, and create a focused Git commit. It formats the single-line message with a Conventional Commits type such as feat, fix, or docs, and checks the resulting status.