2,664 件 ・ 関連度順
概要と使いどころ
Multi-angle review of responses before delivery. Audits from 4 perspectives -- factual accuracy, logical consistency, completeness, and safety. Use for high-stakes responses where errors have real consequences.
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。
Start the Wasp dev server and set up full debugging visibility. This includes running the server (with access to logs), and connecting browser console access so the agent can see client-side errors. Essential for any development or debugging work.
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。
Run and configure oxlint — the high-performance JavaScript/TypeScript linter built on the Oxc compiler stack. Use this skill whenever working in a project that has oxlint installed (check for `oxlint` in package.json devDependencies or an `.oxlintrc.json` / `oxlint.config.ts` config file). This includes when you need to lint code after making changes, fix linting errors, configure oxlint rules/plugins, set up or modify `.oxlintrc.json`, or migrate from ESLint.
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。
QA 纯验收（只测不修）：Mode A 完整验收（test-spec → 10 维度断言引擎 → 报告 + User Gate）；Mode B 供 forge-bugfix P6 调用做单 bug 回归并回填 BF 报告。 铁律：每个测试必须有 pass/fail 和深层断言；console.error 零容忍；不猜端口，只用传入的 app_url。 触发方式：Mode A 用户说"测试"、"QA"、"forge-qa"或 forge-dev 调度；Mode B 由 forge-bugfix P6 调用（传 review_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。
Debug like Fable 5 — systematic root cause analysis with natural reasoning flow. Use this skill when you encounter an error, unexpected behavior, failing tests, or anything that does not work as intended.
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。
Tests in real browsers. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data via Chrome DevTools MCP.
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。
Comprehensive quality control for U.S. patent application filing documents. Use when the user asks to QC, check, validate, or review patent filing documents before submission to the USPTO. Performs 70+ automated and manual checks across specification, drawings, ADS, declaration, assignment, and power of attorney documents. Detects cross-document inconsistencies, formatting issues, missing required fields, and common errors.
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。
Search the web and open-source code for library usage, API syntax, and documentation via Exa. Use this whenever verifying an API signature, looking up how a library is used, checking a config file format, or resolving an error from a third-party dependency -- including when you think you already know the answer, since library APIs drift. Also use for questions documentation cannot answer: release timing, breaking changes, "is X still maintained", licensing, security advisories, and ecosystem comparisons.
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。
Frontend UI design, critique, audit, polish. Use when the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.
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。
Comprehensive code review using specialized agents — orchestrates code, comments, tests, errors, types, and simplify agents sequentially.
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。
Comprehensive code review using specialized agents — orchestrates code, comments, tests, errors, types, and simplify agents sequentially.
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。
Write clean, readable, and maintainable code following principles from Robert C. Martin's "Clean Code" and Object Calisthenics. Use when writing, reviewing, or refactoring code to improve naming, function design, formatting, error handling, and class structure. Includes code smell detection and refactoring guidance.
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。
Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling
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。
Design and review intuitive, scalable, maintainable HTTP APIs. Use this skill whenever the user wants to design a new REST API, review an existing API or spec, write OpenAPI 3.x definitions, or work with HTTP semantics (GET/POST/PUT/PATCH/DELETE), status codes, idempotency (Idempotency-Key), error envelopes (RFC 7807 problem+json), pagination, filtering, versioning, or API auth (API keys, OAuth2 client credentials, rate limits). Also trigger for "API design", "RESTful", "endpoints", "OpenAPI", "Swagger", "ReDoc", "contract testing", or GraphQL and gRPC design questions.
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 find and fix performance problems in applications, frontend and backend, by measuring first. Use this skill whenever the user reports slow endpoints, high latency, poor throughput, memory leaks, large bundles, or slow page loads; wants to profile with cProfile, py-spy, Chrome DevTools, Node --cpu-prof, or perf; run load tests with locust or k6; set performance budgets or SLOs; optimize database queries (EXPLAIN, indexes, N+1); add caching (Redis); improve frontend performance (code splitting, lazy loading, image optimization, memoization, virtualization); or tune the network (CDNs, gzip/br, HTTP/2/3). Also trigger for p50/p95/p99 latency, throughput, error rate, connection pooling, async vs threads, GIL, and memory leak investigations.
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。
Isolate the root cause of ML performance drops, inconsistent evaluations, prediction errors, and training-serving mismatches across data, labels, splits, pipelines, models, metrics, and runtime behavior. Use when investigating a reproducible failure or regression, not routine model selection or general performance validation.
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。
Use when the user shares a Sentry URL, says "check Sentry", or wants to investigate production errors. Uses Sentry MCP tools for deep analysis.
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。
Use BEFORE writing any test — enumerate cases per behavior (happy / boundary / error / abuse), prioritize by likelihood × impact, cross-check via subagent — even if the user just says 'add tests'.
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。
Use when PHPStan, Rector, or ECS output appears — "phpstan says mixed", type errors, "fix code style", "run rector" — even when Eloquent/Laravel/model code is also mentioned.
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。
Use when building an MCP server in Python (FastMCP) or Node/TypeScript (MCP SDK) — agent-centric tool design, input schemas, error handling, and the 10-question evaluation harness.
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。
Use when a diff needs correctness review — null-safety, edge cases, off-by-one, races, error handling — dispatched by /review-changes, /do-and-judge, /judge, even without 'judge'.
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。
Use when the user wants to learn a topic or verify real understanding — rapid-competence session, error drills, learning sprint, gap probe, Feynman check. Triggers 'teach me X', 'quiz me'.
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。
Use when designing or reviewing a form — validation timing, error display, submission lifecycle, optimistic UI, dirty/pristine state, idempotency — even on 'why does submit double-fire?'.
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。
Use when picking a failure-reporting strategy — exceptions vs Result types, recoverable vs not, retry / circuit-breaker / graceful degradation — decision framework only, catalogues externalized.
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。