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概要と使いどころ
Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks
日本語の概要は準備中です。原文の説明を表示しています。
Review a GitHub pull request from multiple perspectives in parallel, output only findings, then let the user pick which to fix in the same session. Use when the user asks to review a PR by number, mentions "PRレビュー" / "PR review" with a number, or invokes `/pr-review <number>`. Fans out subagents for absolute-rules, stop-slop, security, architecture, code-quality, testing, and ai-antipattern.
Accessibility implementation guide for SwiftUI apps. Use when implementing VoiceOver support, adding accessibilityLabel/Hint/Value, supporting Dynamic Type, ensuring color contrast, testing accessibility, or reviewing accessibility in PRs. Covers iOS accessibility APIs, WCAG guidelines, and testing tools.
日本語の概要は準備中です。原文の説明を表示しています。
Verify a released archon binary works end-to-end via a specific install path. Use when: cutting a new release, reproducing a user bug report on the released version, or validating that a hotfix binary actually works after a re-tag. Triggers: "test the release", "test 0.3.1 via brew", "verify the curl install", "smoke test the binary", "did the release binary work", "run /test-release", "verify the release". NOT for: testing dev work (use bun link directly), testing unreleased changes (build locally via scripts/build-binaries.sh first), or running the full validate suite (bun run validate is separate).
日本語の概要は準備中です。原文の説明を表示しています。
Replicate and validate a GitHub issue by spinning up Archon, analyzing the issue, and systematically testing all described symptoms using browser automation. Use when: User wants to reproduce a bug, validate a GitHub issue, confirm a reported problem, or investigate whether an issue is real before working on a fix. Triggers: "replicate issue", "reproduce issue", "validate issue", "confirm bug", "test issue", "can you reproduce", "try to replicate", "verify the bug". Capability: Checks out main, pulls latest, starts Archon, reads the GitHub issue, then uses agent-browser to systematically test every symptom and produce a findings report. NOT for: Fixing issues (use /archon or /exp-piv-loop:fix-issue), general UI testing (use /validate-ui).
日本語の概要は準備中です。原文の説明を表示しています。
Systematically QA test a web application and fix bugs found. Runs QA testing, then iteratively fixes bugs in source code, committing each fix atomically and re-verifying. Use when asked to "qa", "QA", "test this site", "find bugs", "test and fix", or "fix what's broken". Proactively suggest when the user says a feature is ready for testing or asks "does this work?". Three tiers: Quick (critical/high only), Standard (+ medium), Exhaustive (+ cosmetic). Produces before/after health scores, fix evidence, and a ship-readiness summary. For report-only mode, use /qa-only. (gstack) Voice triggers (speech-to-text aliases): "quality check", "test the app", "run QA".
日本語の概要は準備中です。原文の説明を表示しています。
Apply the Red-Green-Refactor cycle to software development. Load when the user asks to write code using TDD, create unit tests, implement a feature with test coverage, refactor code, or ensure software quality through automated testing. Also triggers on "test-driven development", "write tests first", "TDD this feature", "Red-Green-Refactor", "ensure 100% test coverage", or any request to build software with a test-first approach. Supports unit, integration, and end-to-end testing strategies.
日本語の概要は準備中です。原文の説明を表示しています。
Test and debug browser UIs using Chrome DevTools MCP — DOM inspection, console errors, network requests, performance traces, and visual verification. Load when building or debugging anything that renders in a browser, verifying a UI fix, profiling Core Web Vitals in a real page, or the user asks for browser testing with DevTools. Requires chrome-devtools MCP configured. Not for backend-only or CLI work. Pairs with frontend-design and performance-optimization.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
Build robust, production-grade backtesting systems that avoid common pitfalls and produce reliable strategy performance estimates.
日本語の概要は準備中です。原文の説明を表示しています。
Provide comprehensive techniques for penetration testing AWS cloud environments. Covers IAM enumeration, privilege escalation, SSRF to metadata endpoint, S3 bucket exploitation, Lambda code extraction, and persistence techniques for red team operations.
日本語の概要は準備中です。原文の説明を表示しています。
AI-powered E2E web testing — eyes and hands for AI coding tools. Declarative YAML scenarios, Playwright execution, visual matching (OpenCV + OCR), platform auto-detection (Flutter/React/Vue), learning DB. Install: npx skills add ksgisang/awt-skill --skill awt -g
日本語の概要は準備中です。原文の説明を表示しています。
Provide comprehensive techniques for testing REST, SOAP, and GraphQL APIs during bug bounty hunting and penetration testing engagements. Covers vulnerability discovery, authentication bypass, IDOR exploitation, and API-specific attack vectors.
日本語の概要は準備中です。原文の説明を表示しています。
API security testing workflow for REST and GraphQL APIs covering authentication, authorization, rate limiting, input validation, and security best practices.
日本語の概要は準備中です。原文の説明を表示しています。
You are an API mocking expert specializing in realistic mock services for development, testing, and demos. Design mocks that simulate real API behavior and enable parallel development.
日本語の概要は準備中です。原文の説明を表示しています。
Compare cell-type composition and spatial features across conditions in IMC/MIBI cohorts with the patient as the experimental unit, covering pseudoreplication, per-patient aggregation, mixed models, compositional (Dirichlet/scCODA) differential abundance, diffcyt, per-image-to-patient spatial differential testing (SpaceANOVA), batch covariates, and FDR. Use when testing whether a cell type or spatial niche differs between groups, avoiding cell-level pseudoreplication, choosing a differential-abundance method, or correctly powering an IMC cohort comparison.
日本語の概要は準備中です。原文の説明を表示しています。
Controls error rates across thousands of simultaneous tests in genomics discovery using false-discovery-rate methods (Benjamini-Hochberg 1995; Benjamini-Yekutieli 2001 for arbitrary dependence; Storey q-value with pi0 estimation; local FDR; independent filtering Bourgon 2010; covariate-weighted FDR via IHW Ignatiadis 2016), plus family-wise error control (Bonferroni, Holm) and the GWAS genome-wide threshold. Covers the FDR-versus-FWER choice as the discovery-versus-confirmatory distinction, the dependence assumptions behind BH (PRDS) versus BY, pi0 estimation, the independent-filtering and false-coverage-rate traps, and reproducibility ranking via IDR (Li 2011). Use when correcting p-values from genome-wide tests, choosing between BH/BY/q-value/Bonferroni, setting an FDR threshold, applying IHW or independent filtering, or interpreting q-values. For confirmatory trials with few pre-specified endpoints (closed testing, graphical/gatekeeping), see clinical-biostatistics/multiplicity-graphical.
日本語の概要は準備中です。原文の説明を表示しています。
Discovers de novo motifs and tests known motif enrichment in ChIP-seq, ATAC-seq, or other peak sequences using HOMER, MEME-ChIP (STREME, CentriMo, TOMTOM, FIMO), monaLisa, and AME. Handles background selection (GC-matched, dinucleotide-shuffled, Markov order-2, peak-flanks), motif databases (JASPAR 2024 CORE PWMs, JASPAR 2026 deep-learning collection, HOCOMOCO v12, HOMER built-in), centrally-enriched motif testing, and differential motif analysis. Use when identifying TF binding motifs in peaks, testing for known TF enrichment, scanning for motif instances, comparing motif content between conditions, or interpreting motifs from deep learning models.
日本語の概要は準備中です。原文の説明を表示しています。
Working playbook preloaded into the browser-tester helper; the coach updates its Lessons after each round. Use only when acting as browser-tester or coaching it. NOT for general UI work (use matrx-frontend's browser-testing doc).
日本語の概要は準備中です。原文の説明を表示しています。
Expert in web accessibility (WCAG 2.1/2.2 AA/AAA compliance), ARIA patterns, keyboard navigation, screen reader testing, color contrast, focus management, and automated accessibility testing
日本語の概要は準備中です。原文の説明を表示しています。
Expert in statistical analysis for blind A/B and ABX audio testing. Validates randomization, calculates statistical significance, and ensures proper experimental design. Use when implementing A/B test features or analyzing test results.
日本語の概要は準備中です。原文の説明を表示しています。
開発作業ドキュメントを自動生成します。YYYYMMDD_要件名の形式でディレクトリを作成し、requirements.md、design.md、tasklist.md、testing.mdを生成します。「開発作業ドキュメント作成」「新規開発のドキュメント作って」「ドキュメント生成」などで呼び出されます。
新規機能開発の作業ドキュメントを自動生成します。YYYYMMDD_要件名の形式でディレクトリを作成し、requirements.md、design.md、tasklist.md、testing.mdを生成します。「開発作業ドキュメント作成」「新規開発のドキュメント作って」「ドキュメント生成」などで呼び出されます。パフォーマンス改善作業には generate-performance-docs を使用してください。
パフォーマンス改善作業の開発ドキュメントを自動生成します。YYYYMMDD_要件名の形式でディレクトリを作成し、requirements.md、design.md、tasklist.md、testing.mdを生成します。「パフォーマンス改善のドキュメント作って」「最適化作業のドキュメント」「高速化のドキュメント生成」などで呼び出されます。