api

Guides authoring and maintaining agent skills in this repository — enforcing Anthropic best practices, release-version rules, regenerating Cursor rules, and keeping the plugin structure consistent. Use when editing SKILL.md files, reference files, or plugin manifests; creating a new plugin; or reviewing a skill for compliance with authoring standards. Do NOT trigger for general coding tasks, security scanning, or platform API queries.

Use when the user wants to WIRE HawkScan into a CI/CD pipeline config file — triggers on "set up hawkscan in CI", "add stackhawk to my pipeline", "scan in CI", "configure github actions / gitlab / jenkins / circleci for hawkscan", "wire hawkscan into ci/cd", or any provider-named variant. Provider-agnostic: detects the CI system from repo files, edits the pipeline file in place to add a HawkScan job, prompts for HAWK_API_KEY storage in the CI's native secrets store (or an approved external manager), and wires commit-SHA + branch traceability. If no local stackhawk.yml exists yet, still trigger and route the local-config work to the hawkscan skill. Do NOT trigger for: documentation-only changes (e.g. editing a README about CI scanning); informational or research questions ("what CI providers does HawkScan support?"); or running / performing a scan — a local scan is the hawkscan skill, whereas this skill only edits CI pipeline config. Explicit trigger only; no autonomous code-change hook.

Runs the HawkScan DAST security loop — configure, scan, fix all reported vulnerabilities (not just your changes), rescan to verify. Performs code-first discovery to configure high-value scans, and quality-gates every scan against code-derived expectations before findings are parsed. Use when the user asks to run or perform a security/DAST scan, to test an app or API for vulnerabilities, or to verify a vulnerability is fixed; and AUTONOMOUSLY right after you complete a code change (feature, bugfix, refactor) — "done" means "done and secure," so run the loop without asking permission. Do NOT trigger for: informational questions about what HawkScan is, detects, or how it works (e.g. "what vulnerabilities does HawkScan find?"); editing stackhawk.yml or other config without running a scan; querying existing findings, security posture, untriaged counts, or scan history (use the stackhawk-api skill); documentation-only changes; installing or setting up the CLI; or when the user explicitly says to skip scanning.

Analyze a codebase and produce an optimal HawkScan setup — tech flags, scan-policy plugin selection, and stackhawk.yml corrections — then apply it as a non-destructive trial, run ONE trial scan, and promote or discard. Use when the user asks to "optimize my scan", "tune HawkScan", "make my scan faster", "reduce false positives", "pick the right plugins/policy for my app", or invokes /optimize. Also invoked automatically by the hawkscan skill on every fresh stackhawk.yml (Phase 0c) to set up the scan policy + tech flags (Setup mode), and re-runnable anytime via /optimize; the metrics Refine mode is surfaced when a scan is slow. Do NOT use for: a normal security scan or fixing vulnerabilities (use the hawkscan skill); querying existing findings or posture (use the api skill); or editing stackhawk.yml without optimizing/scanning. Requires an onboarded StackHawk app + env and a `hawk` build whose `hawk op` has the `policy` write commands.

Set up checked-in seed data so authenticated HawkScan can reach non-trivial paths. Drives the `hawk perch seed` preflight, designs the minimum seed manifest from the repo digest, then validates and finalizes it via `hawk perch seed validate` / `finalize` — emitting reviewed artifacts under data-seed/ (manifest.yaml, per-service SQL / HTTP / gRPC / Mongo / shell scripts, and a .data-seed-credentials.env handoff hawkscan consumes). Use when the user says "set up data for HawkScan", "my scan has no data to hit", "seed this repo for scanning", or as a first-time-setup step before invoking hawkscan on a fresh repo. NOT autonomous — the user explicitly asks.

Use this skill when a user or agent needs to query the StackHawk platform for security reporting, findings analysis, or app management. Triggers include: "stackhawk api", "security posture", "findings report", "show me findings", "untriaged findings", "which apps", "scan history", "security dashboard", "triage", "what needs attention". Uses the hawk CLI (`hawk op` subcommand) for all platform queries. Do NOT use for running scans (use the hawkscan skill for "scan my app", "hawkscan", "stackhawk.yml", "DAST") or for fixing/remediating code or vulnerabilities — this skill only reads and reports platform data.

Analyze a codebase and produce an optimal HawkScan setup — tech flags, scan-policy plugin selection, and stackhawk.yml corrections — then apply it as a non-destructive trial, run ONE trial scan, and promote or discard. Use when the user asks to "optimize my scan", "tune HawkScan", "make my scan faster", "reduce false positives", "pick the right plugins/policy for my app", or invokes /optimize. Also invoked automatically by the hawkscan skill on every fresh stackhawk.yml (Phase 0c) to set up the scan policy + tech flags (Setup mode), and re-runnable anytime via /optimize; the metrics Refine mode is surfaced when a scan is slow. Do NOT use for: a normal security scan or fixing vulnerabilities (use the hawkscan skill); querying existing findings or posture (use the api skill); or editing stackhawk.yml without optimizing/scanning. Requires an onboarded StackHawk app + env and a `hawk` build whose `hawk op` has the `policy` write commands.

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。