Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Testing & quality
Reviews a code change with three independent reviewers (bugs, the repo's written standards, the spec it came from), tries to disprove each finding, and reports only what holds. Applies chosen fixes to the user's own change; for anyone else's, writes suggestions and can post them as PR comments. Use when the user asks to review, check, or take a second look at a change: "review my changes", "review PR 285" or "!482", "review against DESIGN.md", "is this ready?", review-changes by name, or pasted review findings to handle. Not for whole-repo audits, PR descriptions, explaining a diff, or when the user names another review tool
Analyze code quality based on "Clean Code" principles. Identify naming, function size, duplication, over-engineering, and magic number issues with severity ratings and refactoring suggestions. Use when the user requests code quality checks, refactoring advice, Clean Code analysis, code smell detection, or mentions terms like code review, code quality, refactoring check.
How to author custom PostHog Review skills: the review perspectives, blind-spot checks, validation criteria, and resolution criteria that drive PostHog Review's automated PR reviews. Use when a user wants a new review perspective (a specialist lens on their PRs), a custom blind-spot sweep, their own validation bar for which findings get published, or their own bar for which review comments get implemented. Trigger on "create a PostHog Review perspective", "custom review perspective", "my own blind-spot check", "custom validation criteria", "custom resolution criteria", "tune what PostHog Review publishes", "tune what PostHog Review implements".
Review or refactor React / Next.js code for performance and reliability using a prioritized rule library (waterfalls, bundle size, server/client data fetching, re-renders, rendering). Use when writing React components, Next.js pages (App Router), optimizing bundle size, improving performance, or doing a React/Next.js performance review.
ALWAYS load before starting any task. Provides the 10-dimension weighted scoring rubric (0-10 scale) used to evaluate all implementations in WRFC loops. Dimensions include correctness, completeness, error handling, type safety, security, performance, maintainability, testing, accessibility, and documentation. Includes deterministic validation scripts and score thresholds for pass/revise/reject decisions.
Automate shepherding, checking status, updating branches, and landing open PRs or approved third-party contributor PRs in the flutter/flutter repository using the gh CLI. When to use: - When you need to check the status of open PRs or shepherded third-party PRs. - When you need to update stale branches or apply the 'autosubmit' label to land approved PRs. When not to use: - Do not use for PRs that are not approved (unless they are your own and you want to check status). - Do not use for repositories other than flutter/flutter.
Take a PR from review to merged — run the repo's code-review skill on it in a loop (review, fix, re-review) until nothing is left to fix, applying ALL fixes on the PR branch, wait for CI green, then squash-merge. Use when asked to "ship it", "ship PR #N", or "review, fix and merge" a PR.
Signals scout for PostHog MCP tool calls. Watches `$mcp_tool_call` telemetry for tools that need improvement — broad-reach failure rates, retry hammering, slow or context-bloating responses — grouped by owning product category, each with a fix suggestion.
Validates all CI skills in this repo. Checks Agent Skills spec compliance, gh-aw workflow compilation, permission correctness, and structural conventions. Use when CI skills have been added or modified and you want to verify they compile and conform before committing.
Run the complete test suite in pyramid order - unit, then integration, then E2E. Use when the user asks to run all tests before a PR, run the full test suite with coverage, execute integration and E2E together, generate an HTML test report, or run pre-commit verification across all test tiers.
Use when the user wants to write, debug, or inspect Testplane end-to-end/component tests, work with a Testplane HTML report, inspect Time Travel snapshots, use Testplane CLI/MCP browser tools, or interact with a web app through Testplane.
Use when debugging TypeScript/JavaScript bugs by tracing call chains, understanding unfamiliar codebases quickly, making architectural decisions, or reviewing code quality. Extract function signatures and JSDoc without full file reads, trace call hierarchies up/down, detect code smells, and follow data flow. Triggers on debugging, understanding codebase, architectural analysis, signature extraction, call tracing.
Use when a reported defect must be reproduced as a failing test, when a change to a template or rendered output has to be proved, when a change must be confirmed on a running TYPO3 instance, or when setting up TYPO3 extension tests: unit/functional/E2E, PHPUnit 11-13, mutation testing, final-class mocks (v14), CI matrix across TYPO3 12/13/14.3 LTS, typo3-ci-workflows meta-package, CI failures. Also: testing-framework setup, test matrix, integration/e2e testing, coverage, test generation.
Use when finishing a ticket, feature branch, or pull request and the user asks to validate, demo, verify, sign off, show that it works, run UAT, provide acceptance evidence, or decide whether work is ready to merge. This skill gathers tangible evidence that completed work functions as intended, with videos, screenshots, terminal recordings, JSON responses, output files, logs, and a concise human test guide. Use for web apps, CLI and TUI apps, APIs and SDKs, and native apps including Electron-type apps. Trigger on phrases like "UAT", "verify", "show me it works", "demo this", "walk me through", "ready to merge", "can we merge?", "acceptance test", "validate the changes", "sign off", or any request for proof that a feature branch or PR works.
UX research and design toolkit for Senior UX Designer/Researcher including data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use for user research, persona creation, journey mapping, and design validation.
Review local changes, run or verify validation, decide commit readiness, generate a repo-native commit message, and create the git commit when explicitly requested. Use when preparing or performing a commit, checking code review findings before commit, validating changed files against a spec/plan/test evidence, preventing commits with blocking review or failed tests, or writing a commit message with intent, change, review, and validation evidence.
Visual testing, UI verification, and design comparison using screenshots and Figma integration. Use when the user wants to verify UI appearance, compare with Figma designs, test responsive layouts, check for visual regressions, or validate design implementation.
6-pillar architecture review framework. Adapted from AWS Well-Architected for use by great_cto's architect agent on every non-nano ARCH document. Forces explicit answers across operational excellence, security, reliability, performance, cost, and sustainability — not just feature design.
Audit a white paper or long-form technical document against a research-grounded best-practices checklist. Two lanes — deterministic script checks (readability, undefined acronyms, structure blocks, broken links) plus an LLM-judge review (overclaims, inconsistent numbers, buried lede, limitations honesty, audience fit). Produces a prioritized P0–P2 findings report by default; applies fixes on explicit request (TDD for any code changes). Use when the user says "audit this white paper", "review my paper against best practices", "check this doc for overclaims", "whitepaper QA", "is this paper ready to publish", or wants prioritized recommendations on a technical document.
Autonomous quality meta-skill / "quality brain" (also invocable as /ultracode and /quality-orchestrator aliases). Proactively orchestrates a rigorous, multi-phase quality workflow on any medium/high complexity implementation, review, fix, research, design, audit, or work involving judgment, unknown scope, risk, multiple findings, or non-trivial trade-offs — without the user having to ask. It self-assesses complexity, prefers direct deterministic oracles first, chooses phases (Understand/Design/Review/Research/etc.), composes the right patterns (work-refute with lenses, work-judge, work-exhaust, work-sweep, work-gaps, work-tournament, work-check, work-review), applies all execution mechanics (structured output + retry, worktree isolation, null-handling, concurrency/budget caps, journaling/resume, no silent caps, log/phase via todos), and drives the workflow visibly. The agent is expected to decide on its own at checkpoints (after significant edits, before marking complex todos done, at phase boundaries, when findings accumulate, or when the task language implies "make sure it's solid / thorough / find all issues"). Broad auto-trigger phrases: complex work, implementation, review the changes, audit, design decision, ensure quality, make it robust, thorough review, find all edge cases, etc. The agent can also call the focused skills directly when it identifies the specific need.
Check your work with a verification sub-agent that runs direct oracles first (build/test/typecheck/lint/run-the-app), re-reads the changed code, and returns a schema-validated PASS/FAIL verdict — not prose to grep. Spawns one verifier for small diffs, or parallel lenses (BARRIER) for larger or security/auth/data-boundary changes, then fixes issues and re-verifies under a SEEN ledger until it passes. Use when asked to "check work", "verify changes", "self-verify", "/work-check", "/check", "/verify", or "/self-verify".
Performance optimization, API design & compatibility, security vulnerabilities, and standards spec compliance for workerd code review. Covers tcmalloc-aware perf analysis, compat flags, autogates, web standards adherence, and security patterns. Load this skill when reviewing API changes, performance-sensitive code, security-relevant code, or standards implementations.
Use when the user asks to review, audit, or check the quality of ADVPL/TLPP code for TOTVS Protheus before merge or deploy -- covering best practices (RecLock/MsUnlock pairing, variable scope, area management, error handling), performance bottlenecks, security vulnerabilities (SQL injection, credential exposure), and modernization opportunities (TLPP migration readiness). Also triggers on Portuguese phrasing like "revisar codigo", "revisar fonte", "auditar rotina", "checar boas praticas", "code review advpl", or requests to apply the official TOTVS SonarQube ruleset (CA/BG/CS codes).
Comprehensive API documentation quality checker supporting 7 quality dimensions, SDK source consistency validation, and multi-format reporting. Use for API review, documentation quality assessment, error detection, and consistency checks.
Model Apidog test scenarios: query, create, update, delete, and run test-scenario resources; import endpoint, test-case, or other scenario steps; add scenario reference steps; and orchestrate complex HTTP, condition, loop, wait, script, database, pre/post-action, variable, assertion, extractor, and debugging flows
Lint and format frontend code with Biome 2.4. Covers type-aware linting, GritQL custom rules, domains, import organizer, and migration from ESLint/Prettier. Use when configuring linting rules, formatting code, writing custom lint rules, or setting up CI checks. Triggers on biome, biome config, biome lint, biome format, biome check, biome ci, gritql, migrate from eslint, migrate from prettier, import sorting, code formatting, lint rules, type-aware linting, noFloatingPromises.
create and review ci/cd automation for bruno api tests. use when a user asks to run bruno collections in github actions, gitlab ci, jenkins, azure pipelines, bitbucket, kubernetes, or other pipelines; set up the official bruno github action or the official bruno cli docker image; generate junit, json, or html reports; configure environments, tags, secrets, safe mode, developer sandbox mode, workspace paths, or pull request api-test gates for bruno collections.
File a GitHub issue of type Bug from a description — structures a clear bug report (summary, steps to reproduce, expected vs actual, environment), previews it, then on confirmation creates the issue with the Bug issue type (falling back to a bug label when the repo has no issue types). Use when the user asks to file a bug, open a bug report, create a GitHub bug issue, log a bug, or runs /bug.
Use this skill to run a multi-agent code review of local changes whenever the user asks to "review my code", "review these changes", "do a code review", "check my changes before I commit", "review the whole repo", "review this in the background", or "review this PR I checked out locally" — even if they never say "review" and only ask whether the work is ready to ship or safe to commit. Reviews any local diff, including a pull request checked out into a worktree (`--branch origin/dev`). Prioritizes correctness over nitpicks and writes REVIEW.md. Do NOT use this skill to fetch and review an open PR by number from GitHub (use /review), for a security-specific pass (use /security-review), for grading a SKILL.md file (see rate-skill), or for a quality-only cleanup that does not hunt for bugs (see simplify).
Check and configure API contract testing with Pact, OpenAPI validation, and schema testing. Use when setting up Pact consumer/provider contract tests, configuring OpenAPI request/response validation, adding JSON Schema or Zod schema testing, or detecting breaking API changes in CI. Natural triggers: "set up contract testing", "add Pact", "configure OpenAPI validation".
Check and configure code formatting tools (Biome, Prettier, Ruff format, rustfmt). Use when setting up a formatter for a project, migrating from Prettier to Biome or Black to Ruff, auditing formatter configuration for best practices, adding format-on-save and CI format checks, or standardizing formatting across a monorepo. Natural triggers: "set up formatting", "configure biome", "migrate to ruff format", "add prettier".
This skill should be used when evaluating the quality of book chapters, lessons, or educational content. It provides a systematic 6-category rubric with weighted scoring (Technical Accuracy 30%, Pedagogical Effectiveness 25%, Writing Quality 20%, Structure & Organization 15%, AI-First Teaching 10%, Constitution Compliance Pass/Fail) and multi-tier assessment (Excellent/Good/Needs Work/Insufficient). Use this during iterative drafting, after content completion, on-demand review requests, or before validation phases.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.