variables

Use when running, deploying, or debugging an existing Postman Flow. Distinguishes local graph execution from a deployed webhook, reuses named input scenarios, and follows a run to the failing block rather than treating an HTTP response as whole-flow success. Use for requests such as "why did this flow fail".

Sets up, runs, debugs, and interprets results from `postman application test` — the Postman layer that runs your Playwright tests, captures their network traffic, matches it against a collection contract, runs pm.test assertions, and publishes results to Application Inventory. Covers the Postman side of the integration only — not Playwright test authoring or Playwright failures unrelated to capture. Use when the user asks to "set up application testing," "test my application with Postman," "connect my Playwright tests to Postman," "capture network traffic from Playwright," "Playwright tests are running but nothing shows up in Postman," "why isn't application testing capturing anything," "exclude certain requests from capture," "generate a collection from my app's traffic," "set up application testing in CI," "what API coverage do my e2e tests have," "which APIs are my Playwright tests not hitting."

Use when adding API tests, structural or governance lint, or AI-readiness gates to CI, or publishing reviewed API artifacts to a Postman workspace after merge. Makes contract checks repeatable and separates validation from shared workspace changes. Use for requests such as "run this collection on every PR".

Use when writing or debugging local Postman v3 collection, environment or globals files, including collection lint failures. Preserves the per-entity files, inherited context, and schema shapes that make API changes reusable and reviewable in Git. Use for requests such as "fix this request YAML".

Use when creating or repairing dataset manifests, or when a collection needs queried or joined test inputs, a reusable named view, spreadsheet worksheet data, live database rows, or script access through pm.datasets(). Chooses between a simple iteration file and a dataset while preserving query semantics, portability, and credential boundaries. Use for requests such as "run this collection over database rows".

Use when working through Postman MCP tools to inspect or change workspace resources, choose a targeted operation, or handle MCP limitations. Supports hosted workflows when the CLI is unavailable and distinguishes tool completion from a usable result. Use for requests such as "use Postman MCP to inspect this collection".

Use when initializing Postman in a repository, binding it to a Postman workspace, interpreting what `postman init` did, or handling CLI-suggested actions for authentication, plan, credits, usage quota, or subscription restrictions. Treats the workspace as the place where a service's API work and its evidence live, kept separate from the services it depends on. Use for requests such as "set up Postman in this repo" or "connect this repo to our workspace".

Capture, forward to localhost, replay, and validate webhook deliveries using a reusable public URL. Keep sender configuration across debugging sessions and record arrivals even while local forwarding is stopped, helping distinguish delivery failures from local connectivity issues. Use for implementing or debugging incoming handlers and testing webhooks an API sends, whether or not Postman is mentioned. Example requests include "get payment events to localhost," "inspect a webhook delivery," and "replay an event after a fix"; these illustrate intent, not an exhaustive list or exact phrases to match.

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。