cr-request

You MUST use this when lasting learnings from the current session should be recorded for future agents - pitfalls hit, mistakes the user corrected, conventions found, or commands that finally worked, whatever the conversation language - including when the user asks to write down what the session taught and at the end of the agentflow chain after finalize. Records them without asking in the project's gitignored docs/session-learnings/AGENTS.md; on a separate request, triages the accumulated notes into AGENTS.md, CLAUDE.md, the user's global instructions, or a stronger enforcement such as a check or a test, applying only the approved edits. Not for auditing or restructuring instruction files (maintaining-agent-context). Not for general memory or improvement requests for skills.

You MUST use this when the user asks to take a GitHub issue through the agentflow workflow, with manual stage approvals or a single --auto invocation. Owns intake, clarification, planning, implementation, review, handoff and resumable orchestration. Delivery consumes the installed owner's G3 helpers through explicit current project callbacks and proofs; unknown delivery contracts block their actions. Not for writing a standalone spec, executing an existing plan without issue orchestration, or bypassing project permissions.

You MUST use this when an existing implementation plan is to be executed, either directly in the current session or through subagents, including resuming an interrupted execution from the plan's execution record, or when one or two edits with an obvious approach need doing without a plan. Covers task-by-task execution with evidence, drift handling and blockers, and a resumable execution record. Replaces devflow inline-plan-dev and subagent-plan-dev. Not for writing a plan (plan-craft), checking finished work (verify), acting on review findings (cr-received), or merging, pushing, or opening a pull request (finalize).

You MUST use this when a spec the user approved, an accepted design, or requirements already agreed in the conversation have to be turned into an ordered, multi-step implementation plan before any code is written - including a spec from specify, work with no spec yet, and a plan revision after a document review. Replaces devflow plan-crafting. Covers whether a plan is needed, task order, acceptance-criteria coverage, and the execution choice. Not for open design (specify) or executing a plan (implement).

Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.

Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.

Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".

Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.

This skill should be used when the user wants to "write agent code", "build an agent with ADK", "add a tool", "create a callback", "define an agent", "use state management" — in a project that needs ADK (Agent Development Kit) API patterns and code examples. It provides a quick reference for agent types, tool definitions, orchestration patterns, callbacks, state management, the graph Workflow API, and reference recipes to study. Do NOT use for scaffolding (use google-agents-cli-scaffold) or deployment (use google-agents-cli-deploy).

Set up Claude Code hooks to block dangerous git commands (push, reset --hard, clean, branch -D, etc.) before they execute. Use when user wants to prevent destructive git operations, add git safety hooks, or block git push/reset in Claude Code.

Generate AI music on RunComfy via the `runcomfy` CLI — a smart router across the music-model catalog. Routes to ElevenLabs AI Music Generation (premium 44.1 kHz stereo vocal tracks, 5 s–5 min, $0.0083/s) and ACE Step / ACE Step 1.5 (StepFun-AI open-weights, tag-driven composition, multilingual lyrics, $0.0002–0.0003/s, ~27× cheaper), plus ACE Step audio-inpaint (regenerate a time range inside an existing track) and ACE Step audio-outpaint (extend a track before or after). Picks the right model for the user's actual intent — premium vocal hook, cheap background music library, multilingual pop song, repair a bad chorus, lengthen a 30 s draft into a 2 min cut — and ships each model's documented prompting patterns plus the minimal `runcomfy run` invoke. Triggers on "generate music", "make a song", "AI music", "background music", "instrumental track", "soundtrack", "jingle", "theme music", "royalty-free music", "compose", "music with lyrics", "extend music", "fix this song", "inpaint music", or any explicit ask to generate or edit music.

创建 lark-cli 的自定义 Skill。当用户需要把飞书 API 操作封装成可复用的 Skill（包装原子 API 或编排多步流程）时使用。