Skills
97,501 packaged capabilities and playbooks for agents. Install any of them with one command.
Testing & quality
Drive a live browser from the CLI with playwright-cli to navigate, interact, snapshot, and capture evidence. Use for ad-hoc browser commands, page inspection, screenshots, traces, network mocking, session management, or interactive debugging—not authoring @playwright/test specs. Keywords: playwright-cli, browser automation, live session, snapshot, console, tracing.
Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.
Apply distilled coding principles from 14 classic software books to code review, refactoring, design, and implementation decisions. Do not use for language- or framework-specific tutorials, tool manuals, or tasks already governed by a project's established conventions.
Apply the testing pyramid to a feature — divide test scenarios across levels (unit, integration, e2e), assign each scenario to the cheapest sufficient level, and produce a coverage split per level. Use when asked "unit, integration or e2e?", "what level should this test be?", "how should we test this feature?", "what test coverage do we need?", or to apply the test pyramid to a feature or project.
Generate a QA Sprint Progress Summary Report from Testomat.io TMS data. Use when the user wants to produce a structured end-of-sprint report covering test design coverage, execution results, defect trends, and quality signals. The skill reads data via Testomat.io MCP tools, maps it to the report sections, and outputs an `.html` file by default (or `.md` if explicitly requested).
Enterprise middleware testing patterns for message routing, transformation, DLQ, protocol mediation, ESB error handling, and EIP patterns. Use when testing middleware layers, message brokers, ESBs, or integration buses.
Observability and monitoring validation patterns for dashboards, alerting, log aggregation, APM traces, and SLA/SLO verification. Use when testing monitoring infrastructure, dashboard accuracy, alert rules, or metric pipelines.
Security-first visual testing combining URL validation, PII detection, and visual regression with parallel viewport support. Use when testing web applications that handle sensitive data, need visual regression coverage, or require WCAG accessibility compliance.
Actionable feedback on the quality, usage, and effectiveness of Power BI reports. Automatically invoke when the user asks to "review a report", "audit a report", "report usage analysis", "report health check", "find unused reports", "check if a report is being used", "assess report performance", "evaluate report quality".
Check design-system health for a React+Vite app — raw hex, undefined/unused tokens, scale gaps, DESIGN.md drift, and (opt-in) property→token-family misuse. Use for 'is my design system healthy', 'find raw colors', 'check tokens', or a mixed design system.
Perform language- and framework-specific security best-practice reviews and suggest improvements. Trigger only when the user explicitly requests security best-practice guidance, a security review/report, or secure-by-default coding help. Trigger only for supported languages (python, javascript/typescript, go). Do not trigger for general code review, debugging, or non-security tasks.
Use when the user needs prompt design, optimization, few-shot examples, chain-of-thought patterns, structured output, evaluation metrics, or prompt versioning. Triggers: new prompt creation, prompt optimization, few-shot example design, structured output specification, A/B testing prompts, evaluation framework setup.
Reviews serde serialization code for derive patterns, enum representations, custom implementations, and common serialization bugs. Use when reviewing Rust code that uses serde, serde_json, toml, or any serde-based serialization format. Covers attribute macros, field renaming, and format-specific pitfalls.
Authoritative framework for reviewing any proposed solution (code, config, process, tooling, or architecture decision) before implementation. Covers four core dimensions (effectiveness, side-effects/risks, feasibility, spec compliance) plus five strategic dimensions that catch decision-level failures the core four miss: reversibility calibration (Bezos one-way/two-way doors), failure-mode analysis (FMEA), operability (SRE Production Readiness Review), cost-vs-value (CBAM/WSJF), and team cognitive fit (Team Topologies). Use this skill whenever you need to review, validate, stress-test, or approve a proposed solution, plan, design doc, or approach — before any code is written or change is applied. Triggers — 「审查方案」「方案审查」「评估方案」「方案评估」「review proposal」「方案可行吗」「这个方案靠谱吗」「方案有没有风险」「方案评审」「设计评审」「决策评审」 / solution review, proposal review, design review, decision review, stress-test a plan, validate an approach.
Use this skill to assert Flow emissions in tests with Cash App Turbine. Covers flow.test entry, ReceiveTurbine API (awaitItem, awaitComplete, awaitError, expectMostRecentItem, skipItems, expectNoEvents, cancel and friends, plus the non-suspending takeItem/takeComplete/takeError), turbineScope/testIn for multi-flow tests, the standalone Turbine<T> channel (add/close/asChannel/ensureAllEventsConsumed) for verifying non-Flow callbacks and listeners, the hot vs cold cancellation contract (StateFlow/SharedFlow never auto-complete), Turbine's wall-clock timeout decoupled from runTest virtual time, and the decision matrix between Turbine and raw flow.toList. If the user mentions Turbine, awaitItem, awaitComplete, expectMostRecentItem, takeItem, "test hangs on collect", "SharedFlow never completes", "StateFlow first emission", "TurbineAssertionError", "withTurbineTimeout", "Turbine() channel", "capture a callback in a test", or asserts a ViewModel's StateFlow/SharedFlow, use this skill.
Configure Testomat.io reporting for Java projects that already use Allure. Ask the user whether they want to keep existing Allure annotations and only add Testomat.io reporting or replace Allure annotations with native Testomat.io annotations. If they keep Allure add the testomat-allure-adapter dependency for Maven or Gradle.
Generate a Phase-2 Walkthrough artifact (walkthrough.md) once implementation and verification are complete. Captures a Change Summary, Verification Steps (commands + unit tests + automated browser testing outcomes), Visual Proof (screenshots/recordings embedded directly in the file), and a Review Gate (final diff + PR description for a Git staging-check) so you can catch up on what changed and what's proven to work before merging. Saves to tasks/walkthrough-[feature].md by default. Triggers on: /walkthrough, walkthrough, Phase 2 walkthrough, 生成 walkthrough, 生成走查文档, write the walkthrough.
Adds automated accessibility (a11y) testing to test suites on TestMu AI cloud by enabling WCAG scans through driver capabilities. Framework-agnostic, works with Selenium, Playwright, and Cypress. Use when user mentions "accessibility", "a11y", "WCAG", "accessibility scan", "accessibility testing". Triggers on: "accessibility testing", "a11y scan", "WCAG compliance", "accessibility audit LambdaTest", "is my page accessible".
Audits source code files for AI-generated slop patterns — unnecessary comments, over-engineering, defensive over-coding, AI voice markers, dead code, type workarounds, and verbose patterns. Outputs a structured report with line references and severity. Use when the user wants to find AI slop in specific files, find unnecessary comments, detect over-engineering, or asks "check for slop", "anti-slop", "review for AI patterns". NOT for whole-repo quality audits (that is code-audit's job — or audit-toolkit when unsure which audit fits) and not for prose/README style (humanize-readme).
Apifox Mock data generation specification. Use this skill when you need to generate mock data, Apifox Mock JSON, Apifox Mock scripts, initialize a Mock address, or integrate the Apifox local proxy. It supports Mock.js syntax JSON generation, advanced Mock scripts (field relations, conditional logic, reading request parameters), local mock files, and Mock address initialization for development environments. It covers general rules such as field semantic inference, type tracing, enum recognition, and proxy configuration conventions.
Assess CawPlan version release risk via QA Insights rule engine: compute risk level, structured reasons, suggested actions, and save confirmed assessment to Version. Use when: release risk assessment, can we release, version risk level, 发版风险评估、能不能发版、版本风险、评估发版风险、保存风险结论. NOT for: test execution progress only (use `cawplan-test-execution-progress`); using `cawplan-plan-track` schedule/ticket-completion risk as the A5 conclusion (read-only `release_at`/completion from `versions track` is allowed for display context); defect filing (use `cawplan-defect-ticket`); test plan layout; or ticket QA report release readiness.
Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.
Review changes since a fixed point (commit, branch, tag, PR reference, or merge-base), checking separately whether they follow the repository's recorded coding standards and whether they implement the original issue's requirements. Use when the user asks to review a branch, PR, WIP changes, or changes since a particular point.
Internal prototype QA helper. Use only after a Product Design prototype, URL-to-code build, or image-to-code build has a source visual target and a rendered implementation to compare before handoff. Do not use for broad UX critique, design critique, product audits, or flow reviews; route those user-facing requests to audit.
Master end-to-end testing with Playwright and Cypress to build reliable test suites that catch bugs, improve confidence, and enable fast deployment. Use when implementing E2E tests, debugging flaky tests, or establishing testing standards.
This skill should be used when the user asks to "review code", "review my changes", "check effect patterns", "run effect review", "effect review", "review for effect best practices", or wants a comprehensive code review against Effect-TS conventions, branded types, observability, error handling, test coverage, and UI quality.
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.