azure-sdk-for-js

Route gh-aw workflow design/create/debug/upgrade requests to the right prompts.

Re-record the ai-projects live test suite, push only the recordings whose playback passes to the Azure/azure-sdk-assets repo, and open a PR for the updated assets.json. Use when test recordings are stale, a recorded test fails in playback in CI, or new recorded tests need fresh recordings. Wraps TEST_MODE=record / TEST_MODE=playback runs, dev-tool test-proxy push, and a single-file assets.json PR via the gh CLI.

Migrate Azure/azure-sdk-for-js to a user-specified minimum Node.js version while preserving any existing references above the target.

**UTILITY SKILL** — Must be consulted for SDK development workflow tasks. Routes agents to the correct tools and documentation for building, testing, linting, formatting, provisioning, deploying, and other package development tasks. WHEN: "build package", "run tests", "lint code", "format code", "run checks", "prepare samples", "publish samples", "apply customization", "run migrations", "bump version", "extract API", "update snippets", "check API compatibility", "manage test recordings", "provision test resources", "deploy test resources", "create test resources", "set up test environment", "authenticate to Azure", "login to Azure", "release package", "increment version", "troubleshoot CI", "fix CI failure", "CredScan", "credential scan", "push recordings", "asset sync", "update recordings".

Domain knowledge for Azure AI Content Understanding. Use this skill to answer questions about Content Understanding concepts, analyzers, field schemas, API operations, and JavaScript SDK usage. Always consult official documentation before answering.

Run a specific sample for the Azure AI Content Understanding JavaScript SDK. Use when users want to run a particular sample like analyzeUrl.js or analyzeInvoice.js.

Guide SDK users through setting up their JavaScript / Node.js environment for Azure AI Content Understanding. Use this skill when users need help installing the SDK, configuring Azure resources, deploying required models, setting environment variables, or running samples.

Interactive wizard that walks service teams through creating a package-specific skill for their Azure SDK package. Scans the package, detects customization patterns, scaffolds a SKILL.md with references, and validates with vally lint. The skill is placed inside the package's .github/skills/ directory so find-package-skill discovers it automatically. WHEN: create package skill; add service skill; bootstrap skill for package; new package skill; skill for my SDK package; write skill for search; write skill for cosmos.

**UTILITY SKILL** — Must be consulted before making any changes to packages under sdk/. Discovers and loads package-specific domain knowledge that prevents common mistakes. WHEN: "add feature to package", "fix bug in package", "modify package code", "regenerate from typespec", "change client library".

Apply language-specific post-emitter fixes to ai-projects after a TypeSpec regeneration writes directly into src/ and generated/. Use when reviewing the working-tree diff from `npm run generate:client`, validating the SDK diff against upstream TypeSpec commit descriptions, enforcing protected-file rules, reverting unwanted emitter changes (renames, parameter shapes, model deletions), and preparing the package for build verification. Runs after the regenerate-from-typespec skill.

Commit ai-projects regeneration output to a new branch and open a draft GitHub PR against Azure/azure-sdk-for-js main. Use when the prior five regen skills are complete and you need to push the branch and create a draft pull request via the gh CLI. Stages five logical commits (emitter output, post-emitter edits, samples, tests, changelog). Never force-pushes; always opens as draft.

Regenerate the @azure/ai-projects client from the latest TypeSpec commit on Azure/azure-rest-api-specs. Use when refreshing emitted code, bumping the pinned tsp-location commit, running tsp-client update, or pulling in upstream Foundry spec changes. Handles the rename dance between tsp-location.saved.yaml and tsp-location.yaml, and captures upstream commit descriptions for post-merge validation.

Update ai-projects CHANGELOG.md after a TypeSpec regeneration. Merges new items into the existing top (Unreleased) entry when present; otherwise creates a new top entry, classifying changes into Breaking Changes / Features Added / Bugs Fixed / Other Changes buckets and syncing package.json version as needed.

Domain knowledge for @azure/search-documents. Covers architecture, type conversions, data flow, and common pitfalls. WHEN: regenerate search-documents; modify search-documents; fix search-documents bug; add search-documents feature; search-documents tsp-client update.

Author new samples in samples-dev/ for newly added ai-projects features (agent tools, operations, namespaces). Use when the public API surface (review/ai-projects-node.api.md) gains new classes, methods, or namespaces after a TypeSpec regeneration and example code is needed. Bucket each addition into the right samples-dev/<feature>/ folder and validate with npm run build:samples.

Author skipped Vitest spec files for newly added non-beta ai-projects features under test/. Use when new GA (non-beta) classes, methods, or namespaces appear in review/ai-projects-node.api.md and need test coverage. Generates .skip-ped specs with TODO markers so a human can add recordings, then verifies the file compiles via npm run test:node.