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Testing & security AI Skills

Discover Testing & security skills, compare source repositories and read the instructions for each workflow.

Categories: Testing & security

Showing 58,585–58,608 of 81,973

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GitHub

screenshot-eval

krazyuniks

Evaluate browser screenshots and page state for errors. Use when verifying features work correctly, detecting error conditions, or validating UI state during browser testing.

GitHub

docker-infra

krazyuniks

Docker and Docker Compose configuration and troubleshooting. Use for containers, services, volumes, networking, health checks, and deployment patterns.

GitHub

playwright

krazyuniks

Playwright browser automation and E2E testing. Use for browser testing, screenshots, debugging, MCP tools, page objects, and visual verification.

GitHub

skill-writer

krazyuniks

Create and maintain well-structured Claude Code skills. Use when creating, updating, or improving skills in .claude/skills/.

GitHub

worktree-cli

krazyuniks

Git worktree management with worktree.py CLI. Use for creating worktrees, teardown, merging PRs, syncing branches, and Docker service management.

GitHub

foundry-pr

foundry-works

AI-powered PR creation after spec completion. Analyzes spec metadata, git diffs, commit history, and journal entries to generate comprehensive PR descriptions with user approval before creation.

GitHub

foundry-spec

foundry-works

Spec-first development methodology that creates detailed specifications before coding. Creates structured specs with phases, file-level details, and verification steps. Includes automatic AI review, modificatio...

GitHub

foundry-note

foundry-works

Fast-capture intake queue for ideas and follow-up tasks. Add items quickly, list pending items, or dismiss resolved ones.

GitHub

foundry-test

foundry-works

Systematic test debugging with 5-phase investigation workflow. Use when debugging test failures, investigating complex errors, or when AI consultation would help. Uses native test commands with optional AI cons...

GitHub

foundry-refactor

foundry-works

Safe refactoring operations using LSP for precise symbol resolution. Supports rename, extract function/method, and move symbol operations with automatic reference updates.

GitHub

foundry-review

foundry-works

Review implementation fidelity against specifications by comparing actual code to spec requirements. Identifies deviations, assesses impact, and generates compliance reports for tasks, phases, or entire specs.

GitHub

foundry-research

foundry-works

AI-powered research skill with five workflows - chat (single-model conversation), consensus (multi-model synthesis), thinkdeep (systematic investigation), ideate (creative brainstorming), and deep (multi-phase...

GitHub

foundry-implement

foundry-works

Task implementation skill for spec-driven workflows. Reads specifications, identifies next actionable tasks, and creates detailed execution plans. Use when ready to implement a task from an existing spec - brid...

GitHub

brand-identity

ARTFROST1

Provides the single source of truth for SpecsVibeCode brand guidelines, design tokens, technology choices, and voice/tone. Use this skill whenever generating UI components, styling applications, writing copy, o...

GitHub

react

WallysonGalvao

React/Next.js best practices for modern, performant applications.

GitHub

reviewing-code

WallysonGalvao

Code review workflow for evaluating changes against standards. Use when reviewing pull requests, commits, or diffs.

GitHub

typescript

WallysonGalvao

TypeScript/JavaScript standards for type-safe, maintainable code.

GitHub

writing

WallysonGalvao

Clear writing standards based on Zinsser's principles. Use for documentation, commit messages, PR descriptions, and technical communication.

GitHub

refactor

NB993

TDD의 Refactor 단계 전용 스킬. 테스트가 통과하는 상태를 유지하면서 코드 품질을 개선합니다. 중복 제거, 명확성 향상, 성능 최적화에 사용.

GitHub

infra-tdd

NB993

JpaEntity, Adapter, Repository 클래스를 구현할 때 반드시 사용. 인프라 계층 구현 시 TDD(Red-Green-Refactor) 방식으로 진행. "JpaEntity 구현", "Adapter 구현", "Repository 구현", "영속성 계층" 작업 시 자동 발동.

The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.

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