github.

accessibility-rules

Cross-format document accessibility rule reference with WCAG 2.2 mapping. Use when looking up accessibility rules for Word (DOCX-*), Excel (XLSX-*), PowerPoint (PPTX-*), or PDF (PDFUA.*, PDFBP.*, PDFQ.*) documents, or when mapping findings to WCAG success criteria for compliance reporting.

actionlint

Install, run, and fix errors from actionlint — the GitHub Actions workflow linter. Load when validating `.github/workflows/*.yml` files after migration or generation.

ado-assessment

Review an Azure DevOps organization or project for adherence to Azure DevOps best practices. Use when: running an ADO Quick Review, evaluating org or project configuration, checking adoption of recommended settings, identifying improvement opportunities, ADO best practices, org review, project review.

agent-academy-mission-builder

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agent-academy-report

Generate a full Agent Academy feedback report — extracting feedback from Excel files and GitHub issues, analyzing sentiment, generating charts, and producing a single styled PDF with a cover page, management summary, and detailed analysis. Use this skill when the user asks to generate an Agent Academy report, create a feedback analysis, build a course completion report, or wants to analyze Agent Academy survey data. Also triggers when the user mentions Agent Academy feedback, course grades, sentiment analysis of Agent Academy data, or exporting Agent Academy results to PDF.

agent-academy-stargazers

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agent-framework-py-release

Use when cutting a Python release for the microsoft/agent-framework monorepo. Triggers on "bump py versions", "cut a python release", "prepare release PR for python", "release py packages", "bump python to X.Y.Z", or similar requests to bump Python package versions and prepare a release PR. Handles all four lifecycle tiers (alpha, beta, rc, released) with CHANGELOG-driven selective bumps, floor bound checks, and post-bump validation.

align-cli-webapp-reports

Compare CLI visual readiness report with local webapp report for a given repo, identify differences in checks/rendering/scoring, and fix them

ai-advise

Proactive governance advisor — checks standards, decisions, and quality trends during development. Always advisory, NEVER blocks. Three modes: `advise` (post-edit), `gate` (pre-dispatch), `drift` (on-demand decision audit). Trigger for 'governance check', 'advise on this change', 'check for drift', 'is this aligned with active decisions', 'shift-left advisory'. Not for blocking gates — use /ai-verify. Not for narrative code review — use /ai-review.

ai-animation

Designs motion, transitions, and micro-interactions for UI components: spring animations, gestures, easing, staggers — taste-driven detail compounding. Trigger for 'animate this', 'add transitions', 'micro-interactions for', 'gesture design', 'swipe to dismiss', 'easing for this', 'stagger the'. Not for design systems; use /ai-design instead. Not for visual art; use /ai-visual instead. Not for testing animation code; use /ai-test instead.

ai-autopilot

Delivers large multi-concern specs and backlog runs autonomously: decomposes specs into sub-specs (or normalizes work items into a backlog DAG), deep-plans with parallel agents, builds a dependency DAG, implements in waves, runs a single final quality loop with one bounded quality-remediation pass (verify+guard+review on full changeset), delivers via PR. Trigger for 'implement spec-NNN end to end', 'autopilot this', 'autonomous delivery', 'decompose and ship', 'run the backlog', 'execute these GitHub issues', 'process the sprint backlog'. Invocation is the approval gate. Not for small or single-concern tasks; use /ai-build instead. Not for ambiguous requirements; use /ai-brainstorm first.

ai-board

Operates the project board (GitHub Projects v2 or Azure DevOps): discovers configuration after install (fields, state mappings, process templates) and syncs work-item state at lifecycle transitions. Trigger for 'set up the board', 'configure our ADO board', 'discover board fields', 'move this issue to in-review', 'update the board', 'mark as in progress', 'sync the work item state'. Two subcommands: `discover` (post-install configuration write) and `sync` (lifecycle state transitions). Auto-invoked via `sync` by /ai-brainstorm, /ai-build, and /ai-pr; fail-open. Not for backlog execution; use /ai-autopilot --backlog instead.

ai-brainstorm

Forces rigorous design interrogation BEFORE any code: explores approaches, surfaces ambiguity, gathers evidence, produces an approved spec that becomes the contract for /ai-plan. Trigger for 'lets add X', 'how should we handle Y', 'whats the best approach', 'I am thinking about', 'what should we build for'. Not for existing approved specs; use /ai-plan instead. Not for execution; use /ai-build instead.

ai-branch-cleanup

Cleans branches safely: switches to the default branch, prunes merged and squash-merged branches, syncs to remote, sweeps stale specs, rotates `.ai-engineering/runtime/` per retention policy. Trigger for 'tidy up', 'tidy branches', 'sync to main', 'delete old branches', 'start fresh', 'rotate runtime'. Auto-invoked by /ai-pr after merge. Not for committing changes; use /ai-commit instead. Not for code-level dead-code removal; use /ai-simplify instead.

ai-build

Canonical implementation gateway: reads approved plan.md, resolves stack from manifest, deterministic-routes each task to its adapter, dispatches the build agent in an isolated worktree, runs TDD self-validation per task, then a single final quality loop with one bounded quality-remediation pass on the full changeset before /ai-pr. Trigger for 'go', 'start building', 'execute the plan', 'implement it', 'lets do this', 'build the plan', 'resume', 'continue'. Not without an approved plan; run /ai-plan first. Not for multi-concern specs needing decomposition; use /ai-autopilot instead. Not for a single function or subcomponent; use /ai-code.

ai-code

Writes production code that satisfies stack-context standards on the first pass: interface-first design, backward-compatibility checks, lightweight self-review. Trigger for 'implement this', 'write the code for', 'add X to Y', 'build this function', 'make this work'. Not for tests; use /ai-test instead. Not for debugging; use /ai-debug instead. Not for refactoring; use /ai-simplify instead. Not for executing an approved plan end-to-end; use /ai-build (the gateway).

ai-commit

Runs the governed commit pipeline: auto-branches from protected, stages selectively, formats and lints, scans for secrets, gates docs, composes a conventional message, pushes. Trigger for 'commit my changes', 'save my work', 'push this to remote', 'stage these files', 'ship it'. Not for opening a PR; use /ai-pr instead. Not for branch hygiene; use /ai-branch-cleanup instead.

ai-constitution

Interviews the operator to produce a project-identity CONSTITUTION.md (Mission / Stakeholders / Vocabulary / Prohibitions / Compliance gates / Anti-goals / Boundaries / Escalation / Language / Lifecycle phase). Trigger for 'set up the constitution', 'define project identity', 'who is this project for', 'what does this project never do', 'amend the constitution'. Not for AI-behaviour rules — those live in CANONICAL.md / AGENTS.md. Not for spec governance; use /ai-governance instead.

ai-debug

Diagnoses broken behavior systematically with a 4-phase root-cause loop: test failures, runtime errors, crashes, regressions. Never patches symptoms. Trigger for 'it is not working', 'something broke', 'this used to work', 'I am getting an error', 'CI is failing', 'why is X happening'. Not for adding tests; use /ai-test instead. Not for security findings; use /ai-security instead.

ai-design

Designs user interfaces and design systems for web, mobile, CLI, and documentation-heavy experiences: aesthetic direction, color palettes, typography, spatial composition, information architecture. Trigger for 'design this page', 'create a design system', 'what style should we use', 'UI for this feature', 'color palette for', 'typography for'. Not for animation; use /ai-animation instead. Not for static visual art (posters, banners); use /ai-visual instead. Not for slide decks; use /ai-slides instead.

ai-docs

Manages the documentation lifecycle: CHANGELOG, README, solution-intent architecture docs, external docs portals, and documentation quality gates. Auto-invoked by /ai-pr. Trigger for 'update the changelog', 'the README is stale', 'document this feature', 'docs portal needs updating', 'did we document all changes'. Not for blog or pitch content; use /ai-prose instead. Not for marketing collateral; use /ai-marketing instead.

ai-engineering-issue

Files an upstream bug or improvement report against `arcasilesgroup/ai-engineering` (the framework repo) with strict seven-vector redaction, mandatory human confirmation, and an archived sanitized copy. Trigger for 'report this upstream', 'file an ai-engineering bug', 'this looks like a framework bug', 'tell anthropic / arcasiles about this'. Not for your own project's board (use /ai-issue); not for security disclosure (use the private channel listed in CONSTITUTION.md).

ai-explain

Explains code, concepts, patterns, and architecture with engineer-grade depth: 3-tier control (brief/standard/deep), ASCII diagrams, execution traces, anchored to real file:line references. Trigger for 'how does this work', 'why does it do X', 'trace through this', 'explain this pattern', 'walk me through'. Not for documentation artifacts; use /ai-prose or /ai-docs instead. Not for fixing code; use /ai-debug or /ai-build instead.

ai-explore

Codebase-only read-only research dispatcher. Thin wrapper around the ai-explore agent for architecture mapping, dependency tracing, pattern identification, and risk surfacing. Trigger for 'explore the codebase', 'where does X live', 'map this module', 'what depends on Y', 'trace this import chain'. Not for external evidence with citations; use /ai-research instead.

ai-governance

Validates framework compliance, ownership boundaries, risk acceptance lifecycle, and manifest integrity for regulated environments. Trigger for 'are quality gates enforced', 'who owns this file', 'formally accept a known risk', 'pre-release compliance check', 'governance report for auditors'. Not for code quality; use /ai-verify instead. Not for security scanning; use /ai-security instead — this validates governance process, not code content.

ai-ide-audit

Audits an IDE end-to-end (instruction surface, hooks, skills, agents, installer wiring) using strict file-evidence — never assumptions. Trigger for 'audit IDE support', 'is Copilot wired up correctly', 'check Claude Code integration', 'are there orphaned hooks', 'verify IDE setup'. Accepts Claude Code, GitHub Copilot, Codex, Antigravity, or all. Not for code quality; use /ai-verify instead. Not for security scanning; use /ai-security instead.

ai-issue

Creates a project work-item (issue / task / story) on the user's configured board: routes by manifest `work_items.provider` (GitHub Projects v2 or Azure DevOps), composes title + body + labels, attaches to the active board, and confirms a clickable link. Trigger for 'open an issue', 'file a bug', 'create a task', 'add this to the backlog', 'log a work item'. Not for upstream framework bugs (use /ai-engineering-issue); not for board configuration (use /ai-board discover); not for committing code (use /ai-commit).

ai-learn

Extracts lessons from merged PR review feedback by analyzing what reviewers caught, identifying missed checks, and writing entries directly to LESSONS.md. Trigger for 'the AI keeps doing X wrong', 'learn from this PR', 'what patterns did reviewers catch', 'update our standards from feedback'. Not for in-session observation; use /ai-session-watch instead. Not for skill-level rewrites; use /ai-skill-improve instead.

ai-marketing

Drives go-to-market execution and marketing content: blog posts for distribution, social crossposts, investor materials, market research, outreach campaigns, X/Twitter automation. Trigger for 'go to market', 'marketing plan', 'write a blog post to publish', 'crosspost to socials', 'market research for', 'investor deck', 'outreach campaign', 'content engine'. Not for internal docs; use /ai-docs instead. Not for sprint reviews or solution intent; use /ai-prose instead.

ai-mcp-audit

Audits MCP servers and skills on demand using LLM coherence analysis to catch capability drift and rug-pulls. Trigger for 'audit this skill', 'is this MCP safe', 'check coherence', 'detect rug-pull', 'snapshot baseline', 'mcp audit'. Three modes: scan (declared-vs-observed), audit-update (post-update diff), baseline set (anchor known-good). Not for runtime payload inspection; use prompt-injection-guard hook instead. Not for CVE scanning; use /ai-security instead.

ai-media

Generates images, videos, and audio via AI models (fal-ai MCP): cheap iteration models, expensive production finals, cost-estimate before generation. Trigger for 'generate an image', 'create a thumbnail', 'make a voiceover', 'AI video', 'text to speech for'. Not for design composition; use /ai-visual instead. Not for animation specs; use /ai-animation instead.

ai-note

Saves persistent technical discoveries (debugging insights, non-obvious behaviors, workarounds, integration gotchas) and searches them across sessions. Trigger for 'save this', 'note that', 'remember this finding', 'what did we find about', 'do we have notes on'. Rule of thumb: if it took more than 30 minutes to figure out, save it. Not for cross-session learning patterns; use /ai-session-watch or /ai-learn instead.

ai-onboard

Onboards humans to a project: architecture tours, topic search, decision archaeology, structured new-team-member orientation. Read-only — never modifies code. Trigger for 'where does auth happen', 'what is the architecture here', 'history of this decision', 'onboard me to this repo', 'tour the codebase'. Not for agent session bootstrap; use /ai-start instead. Not for code-level explanation; use /ai-explain instead.

ai-pipeline

Generates, evolves, and validates CI/CD pipelines for GitHub Actions or Azure Pipelines, enforcing SHA pinning, timeouts, secret handling, and concurrency policy. Trigger for 'set up CI/CD', 'add a deployment pipeline', 'is this workflow secure', 'check workflow policy', 'add a security scan to CI'. Not for running pipelines; that is the CI system's job. Not for governance audits; use /ai-governance instead.

ai-plan

Decomposes an approved spec into a phased execution plan with bite-sized tasks, agent assignments, and gate criteria — the contract /ai-build executes. Trigger for 'break this down', 'create a plan', 'what tasks do we need', 'lets start implementing', 'scope changed re-plan'. Hard gate: user approves before /ai-build can run. Not for ambiguous requirements; use /ai-brainstorm instead. Not for execution; use /ai-build instead.

ai-postmortem

Documents production incidents, outages, degradations, and near-misses using the DERP format (Detection, Escalation, Recovery, Prevention) with targeted interview questions per phase. Trigger for 'we had an incident', 'write up the outage', 'something went wrong in prod', 'postmortem', 'near-miss analysis', 'incident report'. Not for customer support investigations; use /ai-support instead. Not for internal dev bugs; use /ai-debug instead.

ai-pr

Creates and updates pull requests with governance: runs the commit pipeline, enforces pre-push gates, generates structured PR body from spec, watches and fixes CI until merged. Trigger for 'open a PR', 'submit this for review', 'I am ready for review', 'merge this into main', 'draft PR', 'update the PR'. Not for commit-only flows; use /ai-commit instead. Not for narrative review; use /ai-review instead.

ai-prompt-tune

Optimizes prompts, system messages, and skill descriptions using explicit-over-implicit, show-do-not-tell, and rationale-embedding techniques. Trigger for 'this prompt is not working', 'optimize this skill description', 'improve triggering', 'rewrite this instruction', 'CSO-optimize'. Pass `--skill name` to optimize any skill's description field. Not for creating new skills; use /ai-scaffold instead. Not for evolving the entire skill body; use /ai-skill-improve instead.

ai-prose

Writes content (blog posts, pitch decks, sprint review summaries, architecture board reports, solution intent documents) with automatic audience targeting (developer/manager/executive). Trigger for 'write a blog post', 'pitch this', 'sprint review summary', 'architecture board doc', 'solution intent for'. Not for documentation artifacts like CHANGELOG or README; use /ai-docs instead. Not for marketing/social content; use /ai-marketing instead. Not for code-level explanations; use /ai-explain instead.

ai-reliability-eval

Measures AI system reliability over time by defining pass/fail criteria before implementation, running capability checks, and tracking regression via pass@k metrics. Trigger for 'how reliable is this', 'did my changes break anything', 'measure AI performance', 'define success criteria', 'eval this feature', 'check skill regression'. Not for code correctness; use /ai-test instead. Not for quality gates; use /ai-verify instead — evals measure AI task completion consistency.

ai-research

External evidence with citations via a 4-tier escalation (local → free MCPs → web/Exa → NotebookLM autonomous deep research, launched first / harvested last). Every claim sourced [N] or marked [unsourced]; output ends with 3 cited recommended directions. Trigger for 'what does the state of the art say about', 'compare options for', 'find sources on', 'investigate this question', 'research this'. Use for questions whose answer lives OUTSIDE the codebase. Not for codebase exploration; use /ai-explore instead. Not for refactors; use /ai-simplify instead. Not for business-logic debugging; use /ai-debug instead.

ai-resolve-conflicts

Resolves git conflicts intent-aware: categorizes by type (lock files, migrations, generated, config, code), regenerates or merges per category, never blindly accepts. Trigger for 'I have conflicts', 'rebase failed', 'merge conflict', 'cherry-pick failed', 'unmerged paths'. Not for branch hygiene; use /ai-branch-cleanup instead. Not for committing the resolution; use /ai-commit instead.

ai-review

Reviews code changes with human-quality judgment: PR reviews, file reviews, diff analysis, architecture feedback. Default mode runs the full specialist roster through 3 macro-agents; pass `--full` for one agent per specialist. Trigger for 'review this', 'give me feedback', 'look over my PR', 'any issues with this', 'is this merge-ready'. Not for evidence-backed gates; use /ai-verify instead. Not for narrative writing; use /ai-prose instead.

ai-scaffold

Creates new ai-engineering skills or agents end-to-end: scaffold, TDD pressure-test, optimize description, register in manifest, sync mirrors. Trigger for 'create a new skill', 'add a slash command', 'the framework needs a capability for', 'build a new agent', 'scaffold a skill for'. Not for evolving existing skills; use /ai-skill-improve instead. Not for description-only optimization; use /ai-prompt-tune instead.

ai-schema

Designs schemas, plans safe migrations with rollback scripts, optimizes slow queries with index recommendations, defines data retention and GDPR right-to-erasure policies. Supports PostgreSQL, MySQL, SQLite, MongoDB. Trigger for 'add a column', 'we need a migration', 'the query is slow', 'define a retention policy', 'GDPR compliance for data'. Not for application-layer ORMs without DB schema; use /ai-code instead. Not for security audits; use /ai-security instead.

ai-session-watch

Observes session corrections, recoveries, and workflow patterns silently, then consolidates them into project-local observations on demand. Trigger for 'start observing', 'learn from this session', 'consolidate observations', 'review what was learned', 'observe this session'. Listening mode is passive; review mode extracts and writes. Not for cross-project learning; use /ai-learn instead. Not for skill rewrites; use /ai-skill-improve instead.

ai-simplify

On-demand code simplification — guard clauses, method extraction, nesting flattening, dead code removal, conditional simplification. Behavior preserved; tests pass after every change. Scoped to operator-chosen files or current diff. No PR, no auto-commit. Trigger for 'simplify this file', 'reduce complexity here', 'clean up the in-flight diff', 'flatten this nesting'. Not for scheduled repo-wide sweeps — use /ai-simplify-sweep. Not for structural changes (file moves, renames) — use /ai-refactor.

ai-simplify-sweep

Sweeps stale code complexity weekly via a scheduled /ai-simplify wrapper, gates the diff, and opens a draft PR for human review. Trigger for 'weekly simplify sweep', 'scheduled simplification', 'simplification sweep', 'simplify pass'. Never auto-merges. Not for in-flight feature work; use /ai-simplify instead. Not for security cleanup; use /ai-security instead.

ai-skill-improve

Improves an existing skill based on real project pain (prior eval corpora under .ai-engineering/evals/, Engram cross-session observations, LESSONS.md, decision-store, instincts, proposals) by analysing the failure pattern, rewriting SKILL.md, and emitting the proposed delta as a PR comment only — no auto-merge. Trigger for 'improve this skill', 'improve /ai-plan', 'make /ai-review better', 'optimize all skills', 'batch improve skills'. Accepts a single skill name or 'all' for batch mode. Not for creating new skills from scratch; use /ai-scaffold instead. Not for platform audit; use /ai-ide-audit instead.

ai-spec-draft

Produces a 14-section spec brief in `.ai-engineering/specs/drafts/<topic>-brief.md` so an operator can hand off a fully-researched problem statement to `/ai-brainstorm`. Trigger for 'draft a spec brief', 'put together a one-pager for this idea', 'research and write up the problem before brainstorming', 'capture the diagnostic for this work'. Not for executing the spec (use /ai-brainstorm → /ai-plan → /ai-build); not for ad-hoc notes (use /ai-note).

ai-sprint

Manages sprint lifecycle: plans a new sprint from backlog, runs data-driven retros comparing planned vs shipped, checks mid-sprint goal status, generates sprint review presentations. Works with GitHub Projects and Azure DevOps. Trigger for 'start sprint planning', 'kick off the sprint', 'lets do the retro', 'what did we deliver last sprint', 'sprint goals check', 'generate the sprint review deck'. Not for daily standup; use /ai-standup instead. Not for solo PR retro; use /ai-learn instead.

ai-standup

Generates standup notes and status updates from actual git commits and PRs — never reconstructed from memory. Trigger for 'write my standup', 'what did I do today', 'what did I ship this week', 'status update', 'handoff notes', 'end of day summary'. Not for pitch or blog content; use /ai-prose instead. Not for sprint retrospectives; use /ai-sprint instead.

ai-start

Bootstraps a coding session: loads project context and displays a welcome dashboard with recent activity, board items, and available commands. Trigger for 'hello', 'lets start', 'good morning', 'whats the status', 'get me up to speed', 'I am back'. Also invokable mid-session to re-bootstrap. Not for human onboarding; use /ai-onboard instead. Not for governance review; use /ai-governance instead.

ai-support

Investigates customer-reported issues with structure: reproduces, traces to code, documents resolution, builds a searchable knowledge base organized by ticket ID. Trigger for 'a user is reporting that', 'customer complaint', 'support ticket', 'investigate this bug report', 'search past support cases'. Not for production incidents; use /ai-postmortem instead. Not for internal dev bugs; use /ai-debug instead.

ai-test

Writes tests, enforces TDD (RED-GREEN-REFACTOR), analyzes coverage gaps, defines test strategy across Python, TypeScript, .NET, Rust, Go. Trigger for 'add tests for', 'write a test', 'I need 80 percent coverage', 'plan my test approach', 'TDD this'. Not for failing tests where the fix is unclear; use /ai-debug instead. Not for AI reliability over time; use /ai-reliability-eval instead.

ai-verify

Use when verification with evidence is needed — not assumptions. Trigger for 'check my code', 'is this ready to merge', 'run the tests', 'is coverage good enough', 'scan for security issues', 'does this meet our standards', 'prove it works', 'is this ready to ship', 'run the release checks', 'pre-release checklist', 'GO/NO-GO'. Runs 2 specialists post-W3 (deterministic, acceptance) with `normal` implicit and `--full` explicit; the `--release` mode flag aggregates 8-dimension release readiness (coverage, security, tests, lint, dependencies, types, docs, packaging) and emits GO/CONDITIONAL GO/NO-GO. For narrative code review with human judgment, use /ai-review instead.

ai-video-editing

Edits real video footage: cuts recordings into highlights, transcribes and structures raw footage, runs FFmpeg operations (trim, concat, reframe, normalize audio), creates Remotion overlays, prepares social-platform cuts. Trigger for 'cut this video', 'edit the recording', 'make a highlight reel', 'reframe for TikTok', 'transcribe this footage'. Not for generating videos from prompts; use /ai-media instead. Not for animation specs; use /ai-animation instead.

ai-visual

Produces static visual design artifacts (posters, banners, flyers, branding pieces, cover art, identity compositions) by composing aesthetic philosophies into HTML/SVG and rendering to PDF/PNG. Trigger for 'create a poster', 'design a banner', 'branding visual', 'marketing graphic', 'cover art for', 'identity composition'. Not for UI interfaces; use /ai-design instead. Not for animation; use /ai-animation instead. Not for presentation decks; use /ai-slides instead. Not for AI-generated photographs; use /ai-media instead.

agentic-workflows

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

analyze-python-api

Analyze the Python weather API, tests, endpoint behavior, and migration scope. Use for extracting routes, payloads, and validation points before C# implementation.

agentic-workflows

Route gh-aw design, creation, diagnosis, patching, active debugging, and upgrade requests to the right strategies.

autoGenesis-run

Execute Appium BDD test scenarios via appium-mcp-server with auto code generation. Use when user provides a scenario name and asks to run, execute, or generate test code for it. Triggers on phrases like "execute scenario X", "run appium test for scenario", "generate test code for scenario", "use autoGenesis-run skill", or when a scenario name is provided alongside a request to automate or test it. Reads scenario steps from .feature files in behave-demo/features/, drives each step through MCP tool calls with persistent retry, then saves generated code via preview_code_changes + confirm_code_changes.

autoGenesis-win

Execute Windows application BDD test scenarios via pywinauto-mcp-server with auto code generation. Use when user provides a scenario name and asks to run, execute, or generate test code for Windows applications. Triggers on phrases like "execute Windows scenario X", "run pywinauto test for scenario", "generate test code for Windows scenario", "use autoGenesis-win skill", or when a scenario name is provided alongside a request to automate or test Windows apps. Reads scenario steps from .feature files, drives each step through MCP tool calls with persistent retry, then saves generated code via preview_code_changes + confirm_code_changes.

acquire-codebase-knowledge

Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.

acreadiness-assess

Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.

acreadiness-generate-instructions

Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.

acreadiness-policy

Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.

ad-campaign-analyzer

Use this skill when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prompts like "analyze my ad campaigns", "where am I wasting ad spend", "reallocate my ad budget", "which ads are actually working", or "ROAS analysis". Do not trigger for campaign planning or creative generation without performance data.

add-educational-comments

'Add educational comments to the file specified, or prompt asking for file to comment if one is not provided.'

adobe-illustrator-scripting

Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.

agent-architecture

Design AI agent architectures through requirements discovery, or audit and diagnose architectural flaws in existing agents. Architecture only; excludes implementation and general code review.

agent-governance

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agent-owasp-compliance

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agent-skill-stack

Find, evaluate, and assemble the smallest compatible set of AI Agent Skills for an end-to-end natural-language goal. Use when a user wants Skills for a multi-step workflow, asks which Skills fit a project, needs an installed-Skill audit or conflict check, has low Skill recall, wants indirect helpers such as humanizers or compliance checks, or wants a project-specific Skill Stack with controlled installation. Search local Skills, registries, GitHub, and OpenCLI; compare adoption, verified fit, safety, and overlap. Do not use for locating one known or common Skill; use the generic find-skills workflow.

agent-supply-chain

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agentic-eval

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agentic-workflows

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

ai-prompt-engineering-safety-review

'Comprehensive AI prompt engineering safety review and improvement prompt. Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness while providing detailed improvement recommendations with extensive frameworks, testing methodologies, and educational content.'

ai-ready

Make any repo AI-ready — analyzes your codebase and generates AGENTS.md, copilot-instructions.md, CI workflows, issue templates, and more. Mines your PR review patterns and creates files customized to your stack. USE THIS SKILL when the user asks to "make this repo ai-ready", "set up AI config", or "prepare this repo for AI contributions".

ai-team-orchestration

Bootstrap and run a lightweight multi-agent development team. Use when starting or adopting a project, planning work, coordinating implementation and optional QA, brainstorming with distinct perspectives, or preserving context across sessions.

anti-ui-slop

Stop coding agents from shipping generic UI. Use UIZZE''s 800,000+ real web and iOS screens to build product-specific interfaces, define a design contract, cover required states, and run a hard finish gate. Use when designing, implementing, redesigning, critiquing, or pre-ship reviewing a web or iOS interface in Codex, Claude Code, Cursor, Copilot, or another coding agent. Trigger with "anti-ui-slop", "stop UI slop", "ground this UI in real screens", or "run the UI finish gate".

api-breaking-change-detector

Cross-references C# Web API controllers/DTOs against their TypeScript/JavaScript consumers (React, Angular, Vue, Svelte, Node.js, or hand-written/auto-generated HTTP clients like Fetch, Axios, NSwag) to catch contract drift in both directions: backend changes that break client applications (renamed/removed JSON keys, new required parameters, status code shifts) and frontend code sending fields the backend no longer reads. Works directly against source code, not exported OpenAPI spec files. Use when the user asks to check for breaking API changes, verify frontend/backend contract sync, or audit a DTO/controller change against its TypeScript/JS consumers before merging. Not for generating new API code from a spec (see openapi-to-application-code) or scaffolding new endpoints (see aspnet-minimal-api-openapi).

appinsights-instrumentation

Instrument a webapp to send useful telemetry data to Azure App Insights

apple-appstore-reviewer

Serves as a reviewer of the codebase with instructions on looking for Apple App Store optimizations or rejection reasons.

arch-linux-triage

'Triage and resolve Arch Linux issues with pacman, systemd, and rolling-release best practices.'

architecture-blueprint-generator

'Comprehensive project architecture blueprint generator that analyzes codebases to create detailed architectural documentation. Automatically detects technology stacks and architectural patterns, generates visual diagrams, documents implementation patterns, and provides extensible blueprints for maintaining architectural consistency and guiding new development.'

arduino-azure-iot-edge-integration

Design and implement Arduino integration with Azure IoT Hub and IoT Edge, including secure provisioning, resilient telemetry, command handling, and production guardrails.

arize-ai-provider-integration

Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features. Supports any LLM provider (e.g. OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM). Use when the user mentions AI integration, LLM provider credentials, create integration, list integrations, update credentials, delete integration, or connecting an LLM provider to Arize.

arize-annotation

Creates and manages annotation configs (categorical, continuous, freeform label schemas) and annotation queues (human review workflows) on Arize. Applies human annotations to project spans via the Python SDK. Use when the user mentions annotation config, annotation queue, label schema, human feedback, bulk annotate spans, update_annotations, labeling queue, annotate record, or human review.

arize-dataset

Creates, manages, and queries Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. Use when the user needs test data, evaluation examples, or mentions create dataset, list datasets, export dataset, append examples, dataset version, golden dataset, or test set.

arize-evaluator

Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and continuous monitoring. Use when the user mentions create evaluator, LLM judge, hallucination, faithfulness, correctness, relevance, run eval, score spans, score experiment, trigger-run, column mapping, continuous monitoring, or improve evaluator prompt.

arize-experiment

Creates, runs, and analyzes Arize experiments for evaluating and comparing model performance. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI. Use when the user mentions create experiment, run experiment, compare models, model performance, evaluate AI, experiment results, benchmark, A/B test models, or measure accuracy.

arize-instrumentation

Adds Arize AX tracing to an LLM application for the first time. Follows a two-phase agent-assisted flow to analyze the codebase then implement instrumentation after user confirmation. Use when the user wants to instrument their app, add tracing from scratch, set up LLM observability, integrate OpenTelemetry or openinference, or get started with Arize tracing.

arize-link

Generates deep links to the Arize UI for traces, spans, sessions, datasets, labeling queues, evaluators, and annotation configs. Produces clickable URLs for sharing Arize resources with team members. Use when the user wants to link to or open a trace, span, session, dataset, evaluator, or annotation config in the Arize UI.

arize-prompt-optimization

Optimizes, improves, and debugs LLM prompts using production trace data, evaluations, and annotations. Extracts prompts from spans, gathers performance signal, and runs a data-driven optimization loop using the ax CLI. Use when the user mentions optimize prompt, improve prompt, make AI respond better, improve output quality, prompt engineering, prompt tuning, or system prompt improvement.

arize-trace

Downloads, exports, and inspects existing Arize traces and spans to understand what an LLM app is doing or debug runtime issues. Covers exporting traces by ID, spans by ID, sessions by ID, and root-cause investigation using the ax CLI. Use when the user wants to look at existing trace data, see what their LLM app is doing, export traces, download spans, investigate errors, or analyze behavior regressions.

aspire

'Aspire skill covering the Aspire CLI, AppHost orchestration, service discovery, integrations, MCP server, VS Code extension, Dev Containers, GitHub Codespaces, templates, dashboard, and deployment. Use when the user asks to create, run, debug, configure, deploy, or troubleshoot an Aspire distributed application.'

aspnet-minimal-api-openapi

'Create ASP.NET Minimal API endpoints with proper OpenAPI documentation'

audit-integrity

Enforce output quality, evidence verification, and quality gates across security audits. Use this skill when you perform SAST, SCA, threat modeling, or security code reviews. Use this skill to verify code locations and taint traces for all findings. Use this skill to prevent the suppression of valid security findings. Use this skill to evaluate reports against quality thresholds (score ≥ 8/10) before delivery.

automate-this

'Analyze a screen recording of a manual process and produce targeted, working automation scripts. Extracts frames and audio narration from video files, reconstructs the step-by-step workflow, and proposes automation at multiple complexity levels using tools already installed on the user machine.'

autoresearch

'Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy''s autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.'

aws-cdk-python-setup

Setup and initialization guide for developing AWS CDK (Cloud Development Kit) applications in Python. This skill enables users to configure environment prerequisites, create new CDK projects, manage dependencies, and deploy to AWS.

aws-cloudwatch-investigation

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aws-cost-optimize

Analyze AWS resources used in the app (IaC files and/or resources in a target account/region) and optimize costs - creating GitHub issues for identified optimizations.

aws-resource-health-diagnose

Analyze AWS resource health, diagnose issues from CloudWatch logs and metrics, and create a remediation plan for identified problems.

aws-resource-query

Query AWS resources using natural language. Covers EC2, S3, RDS, Lambda, ECS, EKS, Secrets Manager, IAM, VPC, networking, messaging, and more. Strictly read-only — no writes, deletes, or mutations.

aws-well-architected-review

Perform an AWS Well-Architected Framework review of the current workload IaC and architecture, generating findings and GitHub issues for improvements.

az-cost-optimize

'Analyze Azure resources used in the app (IaC files and/or resources in a target rg) and optimize costs - creating GitHub issues for identified optimizations.'

azure-architecture-autopilot

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azure-container-registry-cli

Manage Azure Container Registry via the az acr CLI including registries, images, cloud builds, ACR Tasks, authentication, tokens, geo-replication, and networking. Use when working with ACR, az acr commands, pushing/importing/purging container images in Azure, or when the user mentions Azure Container Registry.

address-pr-comments-cecil

Standard workflow to address pull request review comments in Cecil. Use when responding to review feedback, fixing requested changes, or preparing a clear reviewer reply with reproduction, fix, tests, and response.

acronym-check

Ensures abbreviations are expanded on first use per Microsoft style. Use when asked to check acronyms or abbreviations in documentation.

active-voice

Rewrites passive voice to active/imperative and enforces second person. Use when asked to fix passive voice or improve writing directness.

api-consistency

Ensures Azure REST API and CLI consistency across a document. Use when asked to check API calls, CLI parameters, or REST consistency.

ama-logs-update-charts-release-notes

Prepare an ama-logs release PR: bump the image tag (X.Y.Z) across Helm charts, manifests, and Dockerfiles, and add a formatted ReleaseNotes.md entry. Use when: cutting a new ama-logs release, '3.X.Y release notes', 'bump ciprod image tag', 'release PR for Docker-Provider', creating release notes for a new ciprod build. DO NOT USE FOR: MDSD or Windows AMA bumps in isolation, hotfix patches, or anything that does not increment the ciprod image tag.

agentic-workflow-designer

Conversational skill that interviews users to design new agentic workflows

aw-value

Design and verify a deterministic operational-value grader for a GitHub Agentic Workflow. Use for per-run operational value, evidence attribution, maturation, baselines, and operational-value evaluators. Usage: /aw-value OWNER/REPO WORKFLOW-NAME.

awf-release-integrator

Upgrade gh-aw to latest gh-aw-firewall release and identify follow-up spec tasks.

add-llm-provider

Decide and implement how to support a new LLM provider or agent engine in AWF - either as a proxied provider (api-proxy adapter) or a direct-API engine (domain allowlist only), e.g. Cursor, Aider, or any tool that calls its own endpoint.

awf-debug-tools

Practical Python scripts for debugging awf - parse logs, diagnose issues, inspect containers, test domains

awf-skill

Use the AWF (Agentic Workflow Firewall) to run commands with network isolation and domain whitelisting. Provides L7 HTTP/HTTPS egress control for AI agents.

analyze-skill-issues

Query the integration-test storage account to find why a specific skill's tests are failing. Reads blob-stored test result files and surfaces error details. TRIGGERS: why is skill failing, skill test failures, debug skill tests, skill failing tests, analyze skill failures, why are tests failing for skill, skill test errors, investigate skill issues. DO NOT USE FOR: analyzing a GitHub Actions run report or comparing test runs across runs (use analyze-test-run).

analyze-test-run

Analyze a GitHub Actions integration test run and produce a skill invocation report with failure root-cause issues. TRIGGERS: analyze test run, skill invocation rate, test run report, compare test runs, skill invocation summary, test failure analysis, run report, test results, action run report

automate-it

Turns a task you keep doing by hand into a paused GitHub Copilot Automation with an event trigger, a least-privilege tool list, a PARAMETERS + CONTRACT prompt, a quiet exit and a propose-only improver sibling. It creates automations, so it runs only on `/lever automate` or an explicit ask ("automate this", "run this on every PR/issue", "do this nightly", "make this run in the cloud"). When the same task has been done 3 or more times by hand, or a local self-wake has fired 5 or more times for the same job, suggest it in one line instead of running it.

autonomous-delivery

Runs long-lived delivery as a coordinator with parallel lanes. Sets authority and pacing dials up front, keeps lanes alive and fed, lands work through a single-writer release train, and reports status only when something changed. Runs only on `/lever deliver`, "/autonomous-delivery" or an explicit request to run multi-hour, overnight or multi-lane delivery ("run this overnight", "keep N streams going", "don't stop until it ships"), or to re-arm an existing run after a restart.

autonomy-dial

Resolves how far an agent may take a change, from L0 propose to L5 release. It reads the repo's real GitHub rules (rulesets, branch protection, CODEOWNERS, merge queue) and `.github/lever.yml`, applies per-path and per-class limits, records every grant verbatim with its source and expiry, and exposes a `may_merge` check that delivery skills call before landing anything. Use when a delivery skill or automation starts, when creating an automation, before any merge or enqueue, or when the user says "merge", "ship it", "land it", "then merge", "hand off", "do not merge", "freeze" or "you can merge X".

adversarial-review

Review supplied code, a local diff, or a plan by challenging assumptions and delegating an evidence-backed pass to the code-reviewer agent. Use when asked for adversarial review, defect review, or to challenge an implementation. Don't use for writing features, explaining unchanged code, or ordinary factual questions.

accessibility-audit

Audits actual components and routes against applicable WCAG 2.2 A/AA criteria using consumer-owned design-system evidence and repository tools. Use when asked for an accessibility audit, a11y check, keyboard or focus review, contrast check, or screen-reader verification.

add-seed-data

Creates or updates believable deterministic raw fixture scenarios without breaking an existing prototype. Use when asked to add or change fixtures, seed data, sample data, scenarios, or cross-record relationships. Not for UI redesign, live-data infrastructure, or unrelated commands.

agent-browser

Use for explicit agent-browser CLI checks or a named browser capability neither the Copilot canvas nor configured Playwright MCP can supply. Ordinary rendered checks and browser selection belong to browser-canvas-validation.

agent-framework-azure-ai-py

Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.

airunway-aks-setup

Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: \"setup AI Runway\", \"onboard AKS cluster\", \"install AI Runway\", \"airunway setup\", \"deploy model to AKS\", \"GPU inference on AKS\", \"KAITO setup on AKS\", \"run LLM on AKS\", \"vLLM on AKS\", \"set up model serving on AKS\", \"AI Runway controller\".

appinsights-instrumentation

Guidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM best practices.

applicationinsights-web-ts

Instrument browser/web apps with the Application Insights JavaScript SDK (@microsoft/applicationinsights-web). Use for Real User Monitoring (RUM) — page views, clicks, AJAX/fetch dependencies, exceptions, custom events, and browser-side GenAI agent traces correlated to backend OpenTelemetry traces. Covers SDK Loader Script and npm setup, framework extensions (React, React Native, Angular), Click Analytics, telemetry initializers, and OTel GenAI semantic conventions for agent/tool/model spans emitted from the browser.

azure-ai

Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.

azure-ai-agents-persistent-dotnet

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azure-ai-agents-persistent-java

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azure-ai-anomalydetector-java

Build anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.

azure-ai-contentsafety-java

Build content moderation applications with Azure AI Content Safety SDK for Java. Use when implementing text/image analysis, blocklist management, or harm detection for hate, violence, sexual content, and self-harm.

azure-ai-contentsafety-py

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azure-ai-contentsafety-ts

Analyze text and images for harmful content using Azure AI Content Safety (@azure-rest/ai-content-safety). Use when moderating user-generated content, detecting hate speech, violence, sexual content, or self-harm, or managing custom blocklists.

azure-ai-contentunderstanding-py

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azure-ai-document-intelligence-dotnet

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azure-ai-document-intelligence-ts

Extract text, tables, and structured data from documents using Azure Document Intelligence (@azure-rest/ai-document-intelligence). Use when processing invoices, receipts, IDs, forms, or building custom document models.

azure-ai-formrecognizer-java

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azure-ai-language-conversations-py

Implement Conversational Language Understanding (CLU) using the azure-ai-language-conversations Python SDK. Use when working with ConversationAnalysisClient to analyze conversation intent and entities, building NLP features, or integrating language understanding into applications.

azure-ai-ml-py

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azure-ai-openai-dotnet

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azure-ai-projects-dotnet

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azure-ai-projects-java

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azure-ai-projects-py

Build AI applications using the Azure AI Projects Python SDK (azure-ai-projects). Use when working with Foundry project clients, creating versioned agents with PromptAgentDefinition, running evaluations, managing connections/deployments/datasets/indexes, or using OpenAI-compatible clients. This is the high-level Foundry SDK - for low-level agent operations, use azure-ai-agents-python skill.

azure-ai-projects-ts

Build AI applications using Azure AI Projects SDK for JavaScript (@azure/ai-projects). Use when working with Foundry project clients, agents, connections, deployments, datasets, indexes, evaluations, or getting OpenAI clients.

azure-ai-textanalytics-py

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azure-ai-transcription-py

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azure-ai-translation-document-py

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azure-ai-translation-text-py

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azure-ai-translation-ts

Build translation applications using Azure Translation SDKs for JavaScript (@azure-rest/ai-translation-text, @azure-rest/ai-translation-document). Use when implementing text translation, transliteration, language detection, or batch document translation.

azure-ai-vision-imageanalysis-java

Build image analysis applications with Azure AI Vision SDK for Java. Use when implementing image captioning, OCR text extraction, object detection, tagging, or smart cropping.

azure-ai-vision-imageanalysis-py

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azure-ai-voicelive-dotnet

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azure-ai-voicelive-java

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azure-ai-voicelive-py

Build real-time voice AI applications using Azure AI Voice Live SDK (azure-ai-voicelive). Use this skill when creating Python applications that need real-time bidirectional audio communication with Azure AI, including voice assistants, voice-enabled chatbots, real-time speech-to-speech translation, voice-driven avatars, or any WebSocket-based audio streaming with AI models. Supports Server VAD (Voice Activity Detection), turn-based conversation, function calling, MCP tools, avatar integration, and transcription.

azure-ai-voicelive-ts

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azure-aigateway

Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, configure AI backend, token metrics, AI cost control, convert API to MCP, import OpenAPI to gateway.

azure-appconfiguration-java

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azure-appconfiguration-py

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azure-appconfiguration-ts

Build applications using Azure App Configuration SDK for JavaScript (@azure/app-configuration). Use when working with configuration settings, feature flags, Key Vault references, dynamic refresh, or centralized configuration management.

azure-cloud-migrate

Assess and migrate cross-cloud workloads to Azure with reports and code conversion. Supports Lambda→Functions, Beanstalk/Heroku/App Engine→App Service, Fargate/Kubernetes/Cloud Run/Spring Boot→Container Apps. WHEN: migrate Lambda to Functions, AWS to Azure, migrate Beanstalk, migrate Heroku, migrate App Engine, Cloud Run migration, Fargate to ACA, ECS/Kubernetes/GKE/EKS to Container Apps, Spring Boot to Container Apps, cross-cloud migration.

azure-communication-callautomation-java

Build call automation workflows with Azure Communication Services Call Automation Java SDK. Use when implementing IVR systems, call routing, call recording, DTMF recognition, text-to-speech, or AI-powered call flows.

azure-communication-callingserver-java

Azure Communication Services CallingServer (legacy) Java SDK. Note - This SDK is deprecated. Use azure-communication-callautomation instead for new projects. Only use this skill when maintaining legacy code.

azure-communication-chat-java

Build real-time chat applications with Azure Communication Services Chat Java SDK. Use when implementing chat threads, messaging, participants, read receipts, typing notifications, or real-time chat features.

azure-communication-common-java

Azure Communication Services common utilities for Java. Use when working with CommunicationTokenCredential, user identifiers, token refresh, or shared authentication across ACS services.

azure-communication-sms-java

Send SMS messages with Azure Communication Services SMS Java SDK. Use when implementing SMS notifications, alerts, OTP delivery, bulk messaging, or delivery reports.

azure-compliance

Run Azure compliance and security audits with azqr plus Key Vault expiration checks. Covers best-practice assessment, resource review, policy/compliance validation, and security posture checks. WHEN: compliance scan, security audit, BEFORE running azqr (compliance cli tool), Azure best practices, Key Vault expiration check, expired certificates, expiring secrets, orphaned resources, compliance assessment.

azure-compute

Azure VM/VMSS router. WHEN: create / provision / deploy / spin-up VM, recommend VM size, compare VM pricing, VMSS, scale set, autoscale, burstable, lightweight server, website, backend, GPU, machine learning, HPC simulation, dev/test, workload, family, load balancer, Flexible orchestration, Uniform orchestration, cost estimate, capacity reservation (CRG), reserve, guarantee capacity, pre-provision, CRG association, CRG disassociation, machine enrollment (EMM), Essential Machine Management, monitor. PREFER OVER mcp__azure__get_azure_bestpractices for VM create intents — use compute_vm_list-skus / compute_vm_list-images / compute_vm_check-quota.

azure-compute-batch-java

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azure-containerregistry-py

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azure-cosmos-db-py

Build Azure Cosmos DB NoSQL services with Python/FastAPI following production-grade patterns. Use when implementing database client setup with dual auth (DefaultAzureCredential + emulator), service layer classes with CRUD operations, partition key strategies, parameterized queries, or TDD patterns for Cosmos. Triggers on phrases like "Cosmos DB", "NoSQL database", "document store", "add persistence", "database service layer", or "Python Cosmos SDK".

azure-cosmos-java

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azure-cosmos-py

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azure-cosmos-rust

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azure-cosmos-ts

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azure-cost

Azure cost management: query costs, forecast spending, optimize to reduce waste. WHEN: \"Azure costs\", \"Azure bill\", \"cost breakdown\", \"how much am I spending\", \"forecast spending\", \"optimize costs\", \"reduce spending\", \"orphaned resources\", \"rightsize VMs\", \"cost spike\", \"reduce storage costs\", \"AKS cost\". DO NOT USE FOR: deploying resources, provisioning, diagnostics, or security audits.

azure-data-tables-java

Build table storage applications with Azure Tables SDK for Java. Use when working with Azure Table Storage or Cosmos DB Table API for NoSQL key-value data, schemaless storage, or structured data at scale.

add-community-extension

Add a community extension to the Spec Kit catalog from a GitHub issue submission. USE FOR: processing extension submission issues, validating catalog entries, updating catalog.community.json and docs/community/extensions.md, creating PRs. DO NOT USE FOR: creating new extensions from scratch, or first-party extension work.

api-client

Instructions for working on the API client in ./packages/typescript

analyze-ci-failures

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accessibility

Primary accessibility skill for VS Code. REQUIRED for new feature and contribution work, and also applies to updates of existing UI. Covers accessibility help dialogs, accessible views, verbosity settings, signals, ARIA announcements, keyboard navigation, and ARIA labels/roles.

agent-host-chat-contributions

Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.

agent-host-e2e-tests

Use when writing, recording, updating, validating, or troubleshooting Agent Host end-to-end and real-provider integration tests under src/vs/platform/agentHost/test/node/e2e and providerIntegration. Covers adding a cross-provider test, re-recording fixtures after an SDK bump, required cross-platform Azure validation, gating non-deterministic or platform-specific tests, and diagnosing replay cache misses.

agent-host-logs

Analyze Agent Host debug log exports. Use when given an ah-logs or ahp-logs zip/folder, an Export Agent Host Debug Logs bundle, events.jsonl, AHP JSONL transport logs, Agent Host.log, remote-agenthost.log, or copilot-logs.

author-contributions

Identify all files a specific author contributed to on a branch vs its upstream, tracing code through renames. Use when asked who edited what, what code an author contributed, or to audit authorship before a merge. This skill should be run as a subagent — it performs many git operations and returns a concise table.

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

add-command

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add-diagnostic-parser

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add-setting

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ai-docs-autopilot

'End-to-end autopilot: inventory, generate, and submit WDK DDI API reference docs from a CSV file with no user interaction. Use when: running the full doc pipeline unattended, auto-generating and submitting DDI docs.'

ai-docs-generate

'Generate WDK DDI API reference documentation pages from source code and stubs. Use when: writing API docs, generating reference pages, documenting a header, creating DDI documentation.'

ai-docs-inventory

'Inventory and classify APIs listed in a pre-provided CSV for a WDK header file. Use when: inventorying a header, classifying APIs, validating a CSV for doc generation, checking what needs to be documented.'

ai-docs-submit

'Submit generated WDK DDI API reference documentation as a PR to the wdk-ddi repo. Use when: submitting docs, creating a PR for DDI docs, pushing documentation changes.'