Skills
96,981 packaged capabilities and playbooks for agents. Install any of them with one command.
Testing & quality
Use before claiming that work is complete, fixed, or tests have passed, and before committing or creating a PR. You must run verification commands and confirm their output before claiming success; always support claims with evidence.
Use this skill to determine whether a Lightning Web Component (LWC) is accessible and meets WCAG accessibility guidelines. TRIGGER when the user asks \"is my component accessible?\", \"does my LWC meet accessibility guidelines?\", \"is this component WCAG compliant?\", \"find accessibility problems in this LWC\", \"is this LWC keyboard accessible?\", \"does this component work with a screen reader?\", \"does this component have sufficient color contrast?\", \"check ARIA usage in this LWC\", or \"WCAG 2.2 accessibility check\". Also TRIGGER when the user wants to fix or improve accessibility (a11y, WCAG, ARIA) in an LWC's HTML, JS, or CSS — semantic markup, focus, keyboard nav, contrast, screen-reader labels, WCAG 2.2 SC. Produces `a11y-review.md` with WCAG-cited findings. DO NOT TRIGGER for general LWC generation (use `experience-lwc-generate`) or SLDS visual/design review not focused on accessibility (use `design-systems-slds-validate`).
Build and visualize QA dashboards and reports with Allure Report, Grafana, and ReportPortal. Covers test execution visualization, stakeholder-facing quality reports, trend/flakiness panels, release-readiness gates, alerting, and CI integration for automated report generation. Use when: "test dashboard," "Allure," "test report," "quality dashboard," "Grafana," "ReportPortal," "test results visualization." Not for: defining which KPIs to measure or how to interpret them — use qa-metrics (this skill builds the panels; qa-metrics decides what they should show). Related: qa-metrics, ci-cd-integration, ai-bug-triage.
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.
Game QA testing with Playwright — visual regression, gameplay verification, performance, and accessibility for browser games. Use when writing or running game tests, debugging test failures, or building QA infrastructure. This is the reference skill — use qa-game for the user-facing command.
ALWAYS USE for test work that requires changes: write, add, generate, repair, or strengthen tests for existing code in xUnit, MSTest, NUnit, pytest, Vitest/Jest, Go, or another framework. Includes regression cases, failing or flaky tests, coverage-driven additions, and audit-then-fix requests. Focused work stays direct; broad or multi-stage work invokes test-engineer. DO NOT USE for only running tests, analysis-only audits, framework/platform migrations, a test blocked on a missing production seam (testability-obstacle), or MSTest API/configuration corrections that do not design new cases (writing-mstest-tests). Within an active test-engineer pipeline, reuse supplied guidance and do not re-enter this skill.
Runs an autonomous review-and-fix improvement loop over the current branch's changes until a PR review comes back clean, scoped mechanically to the directories the branch touched. Reviews are performed by an installed PR-review skill (default: pr-review-toolkit's review-pr). Use to fix review findings on a branch before opening or updating a pull request ('clean up this branch', 'fix this PR until review passes', 'run review-and-fix on my changes'). NOT for a one-time review — run the PR-review skill directly.
Audit an LLM eval pipeline and surface problems: missing error analysis, unvalidated judges, vanity metrics, etc. Use when inheriting an eval system, when unsure whether evals are trustworthy, or as a starting point when no eval infrastructure exists. Do NOT use when the goal is to build a new evaluator from scratch (use error-discovery, write-judge-prompt, or validate-evaluator instead).
Analyze KiCad projects and PDF schematics: schematics, PCB layouts, Gerbers, footprints, symbols, netlists, and design rules. Reviews designs for bugs, traces nets, cross-references schematic to PCB, extracts BOM data, checks DRC/ERC, DFM, power trees, and regulator circuits. Every finding carries a confidence label and evidence source with trust_summary rollup. Analyzes PDF schematics from dev boards, reference designs, eval kits, and datasheets. Supports KiCad 5–10. Use whenever the user mentions .kicad_sch, .kicad_pcb, .kicad_pro, PCB design review, schematic analysis, PDF schematics, reference designs, Gerber files, DRC/ERC, netlist issues, BOM extraction, signal tracing, power budget, DFM, or wants to understand, debug, compare, or review any hardware design. Also for "check my board", "review before fab", "what's wrong with my schematic", "is this ready to order", "check my power supply", "verify this circuit", OSHWA certification readiness, or any electronics/PCB design question.
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.
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.
TypeScript/JavaScript code quality with ESLint, Biome, and strict TypeScript. Covers linting, formatting, type safety, and best practices. USE WHEN: user works with "TypeScript", "JavaScript", "ESLint", "Biome", asks about "TS strict mode", "type safety", "linting rules", "code formatting" DO NOT USE FOR: SonarQube—use `sonarqube` skill; testing—use Vitest/Jest skills; security—use security skills
Onboard a new QA engineer to an existing codebase, or audit an existing test architecture. Produces a 30-day ramp plan: codebase orientation, framework walkthrough, test architecture audit, mentorship pairing, and first-test guidance. Use when: "QA onboarding," "new tester," "ramp up," "test architecture audit," "first 30 days," "QA mentorship," "joining QA team." Not for: setting up QA on a brand-new project from scratch — use `qa-start`. Related: qa-start, qa-project-context, shift-left-testing, ai-qa-review.
Audit a whole regression suite and prune/restructure it with evidence: per-test coverage fingerprinting, AST near-duplicate clustering, CI-history mining for never-failing and flaky tests, prune decision rules (redundant/obsolete/low-value/keep), smoke/core/extended tiering by risk and defect-detection history, and a defensible "what we deleted and why" record. Deletion is destructive — quarantine and human sign-off are mandatory. Use when: "audit the test suite," "prune redundant tests," "find duplicate tests," "which tests can we delete," "restructure into smoke/core/extended," "is this test pulling its weight," "shrink the regression suite." Not for: Judging whether an individual test is WELL-WRITTEN (smells, assertions) — that is ai-qa-review. Healing one flaky test at runtime — that is test-reliability. Bulk selector regeneration after a UI refactor — that is selector-drift-recovery. Related: ai-qa-review, coverage-analysis, test-reliability, risk-based-testing, qa-project-context.
Generates structured Given/When/Then acceptance criteria for a user story or feature slice, covering the happy path, key failure scenarios, and non-functional expectations in testable form. Use when turning requirements into verifiable scenarios for engineering handoff and QA sign-off. For a dedicated catalog of boundary conditions, error states, and recovery paths across a feature, use deliver-edge-cases; to write the stories themselves, use deliver-user-stories.
Safe-release techniques DURING rollout: feature flags, progressive rollouts, canary analysis, guardrail metrics, production smoke tests, and synthetic users. Bridges QA and SRE practices. Use when: "feature flag testing," "canary deploy," "progressive rollout," "guardrail metrics," "dark launch," "safe rollout." Not for: scheduled probes that run continuously after release — use `synthetic-monitoring`. Not for: designing tests from prod telemetry — use `observability-driven-testing`. Related: release-readiness, synthetic-monitoring, observability-driven-testing, qa-metrics.
One page, automated tier — run the web accessibility (a11y) rule engine against a live page and locate every violation it can mechanically detect. Pass a URL, a config target name (e.g. `accesslint:accessibility-scan dev`), or nothing to use the default target from `accesslint.config.json`. Ensures a debuggable Chrome, runs the @accesslint/core engine over CDP, and returns a worklist of live-DOM WCAG 2.2 violations, each grounded to its DOM selector and source `file:line`. Locates; doesn't edit. Use it for 'is this page accessible', 'check a11y on this URL', 'find contrast and alt-text issues', or to verify a UI change. For hands-on keyboard and screen-reader checks use `accessibility-inspect`; for a whole site or product use `accessibility-audit`; to diff against uncommitted changes or a branch use `accessibility-diff`.
Move quality earlier in the development lifecycle. Covers dev/QA pairing patterns, Three Amigos sessions, TDD facilitation (Red-Green-Refactor), PR review checklists for testability, and Definition of Done with quality gates. Includes shift-left maturity model for team assessment. Use when: "shift left," "TDD," "dev-QA pairing," "definition of done," "testability," "quality culture," "QA in sprint planning." Not for: writing the unit tests themselves — use unit-testing; automated PR test-quality review at scale — use ai-qa-review; multi-quarter QA direction or roadmap — use test-strategy. Related: unit-testing, ai-qa-review, test-strategy.
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.
Test for regulatory compliance: GDPR/CMP consent verification, Google Consent Mode v2, Global Privacy Control (GPC), CCPA/US state opt-out, EU AI Act Article 50 transparency, Better Ads Standards, and cookie-inventory auditing. Covers automated consent-flow testing, policy-based script blocking before consent, and cookie drift detection. Use when: "GDPR test," "compliance," "CMP test," "cookie consent," "consent mode," "CCPA," "GPC," "AI Act," "Better Ads," "privacy banner." Not for: WCAG/axe-core test authoring — use accessibility-testing. Not for: OWASP/vuln scanning — use security-testing. Not for: evaluating your LLM feature's quality or safety — use ai-system-testing. Related: accessibility-testing, security-testing, ai-system-testing, ci-cd-integration.
Validate system resilience through controlled fault injection. Covers hypothesis-driven chaos experiments, failure injection types (network, service, infrastructure, dependency), LitmusChaos/Chaos Mesh/AWS FIS/Gremlin/toxiproxy tooling, automated abort gating, game day planning, and progressive chaos adoption. Use when: “chaos engineering,” “fault injection,” “resilience test,” “game day,” “failure recovery,” “system reliability,” “blast radius.” Not for: safe rollout flags/canary/dark launch during a release — use testing-in-production; designing new tests from production telemetry — use observability-driven-testing. Related: testing-in-production, observability-driven-testing, performance-testing, release-readiness, test-environments.
Migrate a test suite from one framework to another, incrementally and without losing coverage. Covers Selenium→Playwright, Cypress→Playwright, Jest→Vitest, Mocha→Vitest, and Protractor→Playwright, with parallel CI running, locator/assertion translation, and a coverage-parity track. Use when: "migrate tests," "switch framework," "Selenium to Playwright," "Jest to Vitest," "framework migration." Not for: bulk selector regeneration after a UI refactor on the SAME framework — use selector-drift-recovery. Not for: healing one flaky test at runtime — use test-reliability. Not for: modernizing patterns without changing framework — use ai-qa-review. Related: playwright-automation, cypress-automation, unit-testing, ci-cd-integration, test-reliability.
Use when the user asks to "run a deliverability pre-flight before I send", "check my SPF/DKIM/DMARC/BIMI", "why am I landing in spam / promotions", or "score my sender reputation and list hygiene"; runs the one-time pre-send SEND S1 authentication pre-flight and builds the SEND S (Sender-integrity / Deliverability) evidence read — DNS + DMARC-RUA auth, domain/IP reputation, inbox placement, content/link/render, and point-in-time bounce/complaint hygiene — using Pass/Partial/Fail/Unknown/N/A states and scoring only at complete applicable coverage. Not for recurring hygiene trends — use list-hygiene-monitor; not for final EQS or veto verdicts — use email-quality-auditor; not for segments/suppression lists — use list-segment-builder. Email deliverability pre-flight/SPF DKIM DMARC authentication/sender domain reputation
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
Use when writing, reviewing, or committing code to enforce Karpathy's 4 coding principles — surface assumptions before coding, keep it simple, make surgical changes, define verifiable goals. Triggers on "review my diff", "check complexity", "am I overcomplicating this", "karpathy check", "before I commit", or any code quality concern where the LLM might be overcoding.
Use this when you need to EVALUATE OR IMPROVE or OPTIMIZE an existing LLM agent's output quality - including improving tool selection accuracy, answer quality, reducing costs, or fixing issues where the agent gives wrong/incomplete responses. Evaluates agents systematically using MLflow evaluation with datasets, scorers, and tracing. IMPORTANT - Always also load the instrumenting-with-mlflow-tracing skill before starting any work. Covers end-to-end evaluation workflow or individual components (tracing setup, dataset creation, scorer definition, evaluation execution)
You MUST use this when code-review findings, PR comments, CI review output, or reviewer suggestions need technical validation before any fix or disposition, including feedback from human reviewers, subagents, GitHub, static-analysis tools, or external review systems.
Use production telemetry as INPUT to design new tests. Covers OpenTelemetry integration with tests, trace-based assertions, log-informed test creation, production-error analysis for coverage gaps, and telemetry-driven test prioritization. Use when: "trace-based testing," "design tests from logs," "OpenTelemetry assertions," "production errors point to test gaps," "telemetry-driven testing." Not for: safe rollout techniques (flags, canary) during release — use testing-in-production. Not for: scheduled post-deploy probes — use synthetic-monitoring. Not for: triaging CI failures — use ai-bug-triage. Related: testing-in-production, synthetic-monitoring, qa-metrics, ai-bug-triage
Use when the user asks to “QA my conversion tracking before launch”, “check my UTMs / pixel / event firing”, “set up a tracking pre-flight”, or “set the dedup rule so Meta and Google stop double-counting”; builds and fixes the measurement plumbing — conversion-event firing, UTM hygiene, cross-platform dedup rules, attribution-window alignment, and offline/iOS-ATT modeled-gap flags — as a pre-flight checklist plus a UTM/event-spec builder. Not for scoring R1/R2 — that is a scored veto in ad-account-auditor; not for account structure — use campaign-architect. 付费广告转化追踪QA/UTM规范/跨平台去重
Analyze escaped defects and test suite health through blameless postmortems. Covers bug pattern analysis, test suite health reviews, 5 Whys root cause analysis, process improvement cycles, and postmortem/retro meeting templates with action item tracking. Use when: "QA retro," "escaped bugs," "postmortem," "quality incident," "defect analysis," "improvement cycle." Not for: live release go/no-go decisions — use release-readiness. Not for ongoing metric dashboards — use qa-metrics. Not for reviewing existing test code quality — use ai-qa-review. Related: qa-metrics, test-reliability, test-strategy
Use when the user asks to “build the email HTML,” “make this email responsive,” “fix dark-mode rendering,” or “QA the email across clients”; produces the coded HTML build — a responsive table layout, dark-mode and accessibility pass, a client-render matrix, image-block fallbacks, and a plain-text parity check. Not for writing the copy — use email-creative-builder; not for scoring the email or computing EQS — use email-quality-auditor. Email HTML / responsive email / dark-mode rendering
Decision framework for isolating every external dependency in a test suite: when to use in-process mocks, HTTP stubs (MSW, WireMock), record-replay, fault injection (Toxiproxy), or ephemeral real services (Testcontainers), and how to enforce that no real calls escape in CI. Use when: "mock service," "stub API," "fake service," "WireMock," "MSW," "Toxiproxy," "test isolation," "dependency management," "stub an external API in CI." Not for: consumer-driven contract verification (Pact, broker) — use contract-testing; standing up a full Docker Compose env or seed data — use test-environments; broad resilience/game-day fault campaigns — use chaos-engineering. Related: contract-testing, test-environments, api-testing, test-data-management, chaos-engineering.
Build Cypress test suites in TypeScript: E2E tests, component tests, custom commands, cy.intercept network control, cy.session login, Cypress Cloud, and CI integration. Covers retry-ability, the command queue, cross-origin flows with cy.origin, and data-driven testing with fixtures. Use when: "write E2E test in Cypress," "Cypress page object / custom command," "cy.," "cy.intercept," "Cypress component test," "Cypress Cloud," "cypress.config.ts." Not for: Playwright suites — use playwright-automation; flaky-test healing or quarantine — use test-reliability; bulk selector regeneration after a UI refactor — use selector-drift-recovery; Selenium-to-Cypress conversion — use test-migration. Related: playwright-automation, ci-cd-integration, visual-testing, unit-testing, test-reliability.
Use when Codex is building or iterating on a web game (HTML/JS) and needs a reliable development + testing loop: implement small changes, run a Playwright-based test script with short input bursts and intentional pauses, inspect screenshots/text, and review console errors with render_game_to_text.
Scheduled probes that run CONTINUOUSLY after release. Covers probe design for critical user journeys, alerting integration, SLA validation, multi-region monitoring, and the boundary between QA and SRE. Use when: "synthetic monitoring," "uptime testing," "scheduled probes," "SLA validation," "availability monitoring," "post-deploy checks." Not for: safe-release techniques during rollout — use testing-in-production. Not for: designing tests from prod telemetry — use observability-driven-testing. Not for: a one-shot post-deploy smoke gate tied to a release — use release-readiness. Related: testing-in-production, release-readiness, performance-testing, qa-metrics.
Audits font loading, type scales, measure, spacing, OpenType, and rendered punctuation with 78 scoped rules. Use when asked to "audit typography", "fix the fonts", or "review my type system". For a new visual direction use ui-design Direction; for general UI defects use ui-design Audit.
Benchmark throughput and cost-per-token of a model served on vLLM in Chalk's container infrastructure. Use when someone asks for $/token, $/request, tokens/sec, "how much would it cost to self-host this model", GPU sizing for an LLM, or wants to compare a self-hosted model's economics against a hosted API.
Intelligently triage bug reports and error messages by searching for duplicates in Jira and offering to create new issues or add comments to existing ones. When an agent needs to: (1) Triage a bug report or error message, (2) Check if an issue is a duplicate, (3) Find similar past issues, (4) Create a new bug ticket with proper context, or (5) Add information to an existing ticket. Searches Jira for similar issues, identifies duplicates, checks fix history, and helps create well-structured bug reports.
Generates Tzatziki-based Cucumber BDD tests (.feature files) from a functional specification. Use whenever a user wants to write Cucumber tests, add BDD scenarios, create feature files, generate tests, or test application behavior with Gherkin — especially in Java/Spring projects using Tzatziki step definitions for HTTP, JPA, Kafka, MongoDB, OpenSearch, logging, or MCP. Also use when the user mentions integration, acceptance, or end-to-end tests in a project that already has Tzatziki/Cucumber dependencies, including TestNG-based setups
Validate that analytics and marketing tracking fire CORRECTLY: GA4/GTM dataLayer events, Meta/TikTok/LinkedIn pixels, and ad-tech tags. Covers building a tracking plan as the contract, intercepting collect-endpoint beacons and dataLayer.push in Playwright, asserting event name + params + values + timing + de-duplication, Consent Mode v2 gating, CI regression gating, and news-media events (article-view, scroll-depth, paywall). Use when: "test analytics tracking," "GA4 event test," "verify the pixel fires," "dataLayer test," "tracking plan," "Meta Pixel dedup," "scroll-depth tracking test," "gate tracking in CI." Not for: whether tracking is ALLOWED to fire under consent law (GDPR/CMP) — that is compliance-testing; this skill checks the data is CORRECT. SEO meta tags / structured data — out of scope. Related: compliance-testing, playwright-automation, api-testing, qa-project-context.
Enforce the no-useEffect rule when writing or reviewing React code. ACTIVATE when writing React components, refactoring existing useEffect calls, reviewing PRs with useEffect, or when an agent adds useEffect "just in case." Provides the five replacement patterns and the useMountEffect escape hatch
Bulk-regenerate broken test selectors after a UI refactor or redesign. Detects drift between old and new DOM with an aria-snapshot diff, maps old locators to new equivalents using role-first + region scoping, validates against the new build, and produces a single PR with grouped per-file selector updates and per-change evidence. Assumes Playwright >= 1.50 (trace viewer DOM-snapshot panel, getByRole filtering, ariaSnapshot). Use when: "UI refactor broke tests," "redesign broke tests," "bulk update selectors," "regenerate selectors after refactor," "selector drift," "fix N broken tests after redesign." Not for: healing one flaky test at runtime — use test-reliability. Not for: writing a new test suite from scratch — use playwright-automation. Not for: re-recording tests after a framework switch (Selenium to Playwright) — use test-migration. Related: test-reliability, playwright-automation, test-migration, ci-cd-integration, visual-testing.
Audits instrumentation health of existing Arize traces. Runs deterministic checks over a bounded span sample (orphaned/uncategorized/duplicate spans, flat structure, blank root I/O, unset status, missing token counts or children) and returns a ranked report. Use when the user asks why traces look empty/flat/broken, wants to verify instrumentation is healthy, find instrumentation issues, or why evals or token/cost dashboards show n/a or zero. To debug app behavior or errors, use arize-trace.
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.