LabscoMCP early access ↗

Agent Skills

Instruction packs for your AI agent — browse standalone skills, tool add-ons and skills that need setup first.

✦ Standalone skills2,358

Listed for general use, with no separate prerequisite named.

🧰 Tool add-ons426

Listed as skills bundled with a specific tool, with no separate prerequisite named.

🔌 Needs setup first88

Each relies on something you set up separately — such as an app, a command-line tool or an account — and its page names what that is.

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google-labs-code · Testing & QA

71 standalone skills
anthropics avatar

webapp-testing

✓★ 158,491

by Anthropic

Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

AI impact score: 4 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
mattpocock avatar

migrate-to-shoehorn

✓★ 157,694

by mattpocock

Migrate test files from `as` type assertions to @total-typescript/shoehorn. Use when user mentions shoehorn, wants to replace `as` in tests, or needs partial test data.

AI impact score: 2 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
mattpocock avatar

setup-pre-commit

✓★ 157,694

by mattpocock

Set up Husky pre-commit hooks with lint-staged (Prettier), type checking, and tests in the current repo. Use when user wants to add pre-commit hooks, set up Husky, configure lint-staged, or add commit-time formatting/typechecking/testing.

AI impact score: 4 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
microsoft avatar

playwright-component-testing

✓★ 97,294

by microsoft

Set up component testing with Playwright using a story gallery — scaffold stories and a gallery dev page driven by the built-in mount fixture, no dedicated component-testing runtime. Use when asked to test React or Vue components in isolation with Playwright, or to migrate off @playwright/experimental-ct-react / -vue.

openai avatar

bootstrap-realtime-eval

✓★ 74,559

by openai

Bootstrap a new realtime eval folder inside this cookbook repo by choosing the right harness from examples/evals/realtime_evals, scaffolding prompt/tools/data files, generating a useful README, and validating it with smoke, full eval, and test runs. Use when a user wants to start a new crawl, walk, or run realtime eval in this repository.

AI impact score: 2 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

agentic-eval

✓★ 36,202

by github

Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality

AI impact score: 4 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

breakdown-test

✓★ 36,202

by github

Test Planning and Quality Assurance prompt that generates comprehensive test strategies, task breakdowns, and quality validation plans for GitHub projects.

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

csharp-mstest

✓★ 36,202

by github

Get best practices for MSTest 3.x/4.x unit testing, including modern assertion APIs and data-driven tests

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeSetup details
github avatar

csharp-nunit

✓★ 36,202

by github

Get best practices for NUnit unit testing, including data-driven tests

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

csharp-tunit

✓★ 36,202

by github

Get best practices for TUnit unit testing, including data-driven tests

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

csharp-xunit

✓★ 36,202

by github

Get best practices for XUnit unit testing, including data-driven tests

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

eval-driven-dev

✓★ 36,202

by github

Improve AI application with evaluation-driven development. Define eval criteria, instrument the application, build golden datasets, observe and evaluate application runs, analyze results, and produce a concrete action plan for improvements. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.

AI impact score: 4 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

java-junit

✓★ 36,202

by github

Get best practices for JUnit 5 unit testing, including data-driven tests

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

javascript-typescript-jest

✓★ 36,202

by github

Best practices for writing JavaScript/TypeScript tests using Jest, including mocking strategies, test structure, and common patterns.

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

playwright-explore-website

✓★ 36,202

by github

Website exploration for testing using Playwright MCP

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

playwright-generate-test

✓★ 36,202

by github

Generate a Playwright test based on a scenario using Playwright MCP

AI impact score: 4 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

pytest-coverage

✓★ 36,202

by github

Run pytest tests with coverage, discover lines missing coverage, and increase coverage to 100%.

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

quality-playbook

✓★ 36,202

by github

Run a complete quality engineering audit on any codebase. Derives behavioral requirements from the code, generates spec-traced functional tests, runs a three-pass code review with regression tests, executes a multi-model spec audit (Council of Three), and produces a consolidated bug report with TDD-verified patches. Finds the 35% of real defects that structural code review alone cannot catch. Works with any language. Trigger on 'quality playbook', 'spec audit', 'Council of Three', 'fitness-to-purpose', or 'coverage theater'.

AI impact score: 4 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

react18-enzyme-to-rtl

✓★ 36,202

by github

Provides exact Enzyme → React Testing Library migration patterns for React 18 upgrades. Use this skill whenever Enzyme tests need to be rewritten - shallow, mount, wrapper.find(), wrapper.simulate(), wrapper.prop(), wrapper.state(), wrapper.instance(), Enzyme configure/Adapter calls, or any test file that imports from enzyme. This skill covers the full API mapping and the philosophy shift from implementation testing to behavior testing. Always read this skill before rewriting Enzyme tests - do not translate Enzyme APIs 1:1, that produces brittle RTL tests.

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

react19-test-patterns

✓★ 36,202

by github

Provides before/after patterns for migrating test files to React 19 compatibility, including act() imports, Simulate removal, and StrictMode call count changes.

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

scoutqa-test

✓★ 36,202

by github

This skill should be used when the user asks to "test this website", "run exploratory testing", "check for accessibility issues", "verify the login flow works", "find bugs on this page", or requests automated QA testing. Triggers on web application testing scenarios including smoke tests, accessibility audits, e-commerce flows, and user flow validation using ScoutQA CLI. Use this skill proactively after implementing web application features to verify they work correctly.

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

spring-boot-testing

✓★ 36,202

by github

Expert Spring Boot 4 testing specialist that selects the best Spring Boot testing techniques for your situation with Junit 6 and AssertJ.

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

unit-test-vue-pinia

✓★ 36,202

by github

Write and review unit tests for Vue 3 + TypeScript + Vitest + Pinia codebases. Use when creating or updating tests for components, composables, and stores; mocking Pinia with createTestingPinia; applying Vue Test Utils patterns; and enforcing black-box assertions over implementation details.

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
github avatar

webapp-testing

✓★ 36,202

by github

Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

AI impact score: 4 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
anthropics avatar

m5-onboard

✓★ 31,611

by anthropic

End-to-end onboarding for a freshly-plugged-in M5Stack ESP32 device (Cardputer, Cardputer-Adv, Core, CoreS3, Stick) — detect on USB, flash UIFlow 2.0 firmware, and install the Claude Buddy MicroPython app bundle. Use whenever the user plugs in or wants to flash/provision/reset an M5Stack or ESP32 board, or says "m5-onboard go".

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
openai avatar

runtime-behavior-probe

✓★ 27,670

by openai

Plan and execute runtime-behavior investigations with temporary probe scripts, validation matrices, state controls, and findings-first reports. Use only when the user explicitly invokes this skill to verify actual runtime behavior beyond normal code-level checks, especially to uncover edge cases, undocumented behavior, or common failure modes in local or live integrations. A baseline smoke check is fine as an entry point, but do not stop at happy-path confirmation.

AI impact score: 3 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.Access detailsSetup details
mastra-ai avatar

debugging-difficult-bugs

★ 25,837

by mastra-ai

Use early when debugging a medium or hard bug, especially when tests alone may not reveal the real runtime failure. Trigger this before extended TDD iteration when a bug involves runtime state, ordering, persistence, streaming, concurrency, UI/manual reproduction, external services, or when a red or newly passing test may not model the real issue. Skip only when the root cause is already directly proven by a stack trace or deterministic test that exercises the real runtime path.

AI impact score: 4 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
mastra-ai avatar

pr-explainer

★ 25,837

by mastra-ai

Use when creating an approachable, self-contained HTML review aid for a pull request; explaining what changed, why it matters, how it works, and how it fits into the broader system; turning PR diffs, commits, tests, and architecture context into a local `.pr-review/` HTML page for reviewers; or helping reviewers understand complex code changes without dumping the full diff.

langchain-ai avatar

code-review

★ 25,749

by langchain-ai

Perform a structured code review of changes, checking for correctness, style, tests, and potential issues.

AI impact score: 4 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
openai avatar

hatch-pet

✓★ 23,283

by openai

Create, repair, validate, visually QA, and package Codex-compatible animated pets and pet spritesheets from character art, generated images, company or prospect brand cues, or visual references. Use when a user wants a lightweight-worker Codex pet workflow, a non-pixel custom pet style, a prospect or company mascot pet, or a full 8x9 animated pet atlas with transparent unused cells, QA contact sheets, and pet.json packaging. This skill composes the installed $imagegen system skill for visual generation and uses bundled scripts for deterministic spritesheet assembly.

AI impact score: 2 out of 5 for usefulness, based on documentation; the AI did not install or run the tool. See “Impact rating (1–5)” on the “How to read ratings & labels” page.FreeInstallation
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