Delegation mode for open-code-review (OCR). Instead of OCR calling an LLM endpoint, this skill instructs the host agent to perform the code review itself, using OCR only for deterministic engineering: file selection and rule resolution. Use when the host agent should drive the review with its own LLM capabilities.
Performs AI-powered code review on Git changes using the ocr CLI from alibaba/open-code-review. Use when the user asks to review code, review a pull request, review staged/unstaged changes, review a commit, or compare branches for code quality issues. Produces line-level review comments and can automatically apply…
Hotspot-first, multi-pass code review for pull requests, branches, pasted diffs, and work-in- progress changes. Models behavior changes, selects risky hotspots, acquires minimal local context, generates candidate findings and questions, runs a skeptic pass and dedup, then surfaces at most 5 high-signal outputs.…
Use when the user needs ideas or a name — brainstorming, naming, developing an idea further, hybridizing ideas, stress-testing candidates, reframing a problem, or picking a final direction. Ideas persist in a per-topic logbook across sessions.
Design and create a logbook — a shared, queryable, schema-stable working surface that agents and humans append to, annotate, and query across sessions. Invoke when the user explicitly wants to track structured entries across multiple sessions or multiple contributors (e.g. "I want to track X across sessions", "I need…