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概要と使いどころ
Build evidence-backed day trips, multi-day itineraries, and efficient stop sequences with Google Maps data through the standalone CLI. Use when the desired output is a practical travel plan, not merely a route or list of places.
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Search places, resolve addresses, compare routes, inspect neighborhoods, and retrieve geographic or environmental facts through the standalone @cablate/mcp-google-map CLI. Use for concrete location questions; use the travel-planning or local-seo Skill for those specialized outcomes.
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 ONLY when the user says they do not know which master or which teaching mode to use — 不知道问谁, 该找哪位祖师, 该用哪个模式, 有哪些法师, which master should I ask, help me choose. This is a router, not a teacher: it names a destination and stops. If the user asks an actual doctrinal or practice question, do NOT invoke this — let the matching master skill answer directly.
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。
Entry point + orchestrator for the recomby-geo GEO (Generative Engine Optimization) workflow on OpenAI Codex CLI. Use when the user wants to run any stage of the GEO pipeline on a client folder — intake, visibility audit, content-gap analysis, content brief, draft production, distribution, or monthly re-audit — or asks to "run GEO", "audit AI search visibility", or "GEO this client". Codex has no bare slash commands, so this skill is how the 7 stages (that Claude Code runs as /01-intake … /07-reaudit) are driven on Codex. It routes to the per-stage specs in this plugin's commands/ and enforces the orchestration rules. Does not auto-fill expert content — the human-in-loop brief checkpoint is the moat.
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。
根据 model_route.json、数据计划和清洗数据，为数学建模论文生成结果证据契约和 q1/q2/q3 建模代码脚手架。Invoke when 需要把模型输出、评价指标、结构化结论、论文表格和当前赛题专用建模代码沉淀到 paper_output/results/、paper_output/tables/ 和 paper_output/code/modeling/，供 QA 与正文生成读取。
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 you need to design, review, or improve security in Micronaut applications — including micronaut-security authentication, @Secured and intercept-url-map rules, JWT/session strategies, SecurityService checks, CORS, CSRF awareness for browser apps, rejection handlers, and sensitive-data-safe logging. This should trigger for requests such as Add Micronaut security support; Review Micronaut security configuration; Improve API authorization in Micronaut; Add JWT security in Micronaut; Harden Micronaut route authorization rules. Part of Plinth Toolkit
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 you need to design, review, or improve REST APIs with Micronaut — including @Controller routes, HTTP status codes, DTOs, Bean Validation, exception handlers, pagination, idempotency, ETag/If-Match, caching headers, versioning, contract-first OpenAPI (OpenAPI Generator), optional runtime OpenAPI via micronaut-openapi, and security annotations. This should trigger for requests such as Review or improve Micronaut @Controller REST APIs; Add validation, error handling, or align controllers with the OpenAPI contract on Micronaut HTTP layer; Design Micronaut controllers and DTO validation; Add Micronaut exception handlers and Problem Details responses; Improve pagination filtering or OpenAPI alignment in Micronaut APIs. Part of Plinth Toolkit
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。
Routes Maven version questions to the right workflow by choosing project-local update report interpretation for a user’s own pom.xml, or Maven artifact discovery from maintainer-approved structured evidence. Use when interpreting dependency, plugin, or property update reports; finding Maven coordinates; verifying groupId artifactId version; browsing versions from approved evidence; or constructing artifact URLs without fetching remote content. Part of Plinth Toolkit
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。
Execute one bounded RED to GREEN experiment from bead or caller intent; return derived subject identity and check facts. Triggers: "implement", "implement this bead", "run the experiment". Full plan-to-validation requests route to rpi.
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。
Request router: picks the agent, skill, and pipeline with /do's rules, then uses Jev to validate the requested outcome and attach extra skills.
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。
Classify user requests and route to the correct agent + skill. Primary entry point for all delegated 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。
Implement authentication and authorization using @delon/auth. Use this skill when adding login/logout flows, JWT token management, role-based access control (RBAC), route guards, HTTP interceptors, and session management. Integrates with Firebase Auth and custom permission systems. Ensures secure token storage, automatic token refresh, and consistent authorization checks across components and services.
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。
This skill should be used when analyzing binaries, executables, or bytecode to understand what they do or how they work. Triggers on "binary", "executable", "ELF", "what does this do", "reverse engineer", "disassemble", "decompile", "pyc file", "python bytecode", "analyze binary", "figure out", "marshal". Routes to sub-skills for triage, static analysis, dynamic analysis, synthesis, or tool setup.
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。
This skill should be used when working with CSS, creating components, styling elements, refactoring styles, or reviewing CSS code. Triggers on "CSS", "styles", "Tailwind", "dark mode", "component styling", "semantic class", "@apply", "stylesheet". Routes to specialized sub-skills for creation, validation, or refactoring.
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。
This skill should be used when implementing features with parallel exploration or competition. Triggers on "build", "create", "implement", "try both approaches", "compare implementations". Routes to omakase-off (entry gate for design exploration) or cookoff (exit gate for parallel implementation).
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 15 애플리케이션을 위한 프론트엔드 개발 가이드라인. React 19, TypeScript, Shadcn/ui, Tailwind CSS를 사용한 모던 패턴. Server Components, Client Components, App Router, 파일 구조, Shadcn/ui 컴포넌트, 성능 최적화, TypeScript 모범 사례 포함. 컴포넌트, 페이지, 기능 생성, 데이터 페칭, 스타일링, 라우팅, 프론트엔드 코드 작업 시 사용.
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。
Split a multi-call LM workflow by cognitive load, not by accuracy: let one strong model make the few reasoning decisions and a cheap model do the many mechanical executions (Aider architect+editor, DSPy optimizer-LM vs task-LM, vLLM speculative draft+target, LangGraph supervisor+worker are the same shape). Use when designing or cost-optimizing a pipeline that calls an LM many times, when deciding which steps need a strong reasoner vs a cheap executor, or when adding an escalation valve for when the cheap tier degrades. Search keywords: reduce LLM cost, cheaper model, lower token cost, model cascade, route to cheap model, strong model plus cheap model, LLM cost 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。
Operating-system distillation of LlamaIndex — the leading RAG / document-agent framework. Activate when the calling agent must build, debug, harden, or evaluate a Retrieval-Augmented Generation pipeline over unstructured/private data, decide between RAG primitives (Index types, retrievers, query engines, routers, agents), or pick LlamaIndex vs LangChain / Haystack / raw vector store for a coding task. Encodes the 5-layer mental model (Documents → Nodes → Indices → Retrievers → Query Engines / Response Synthesizers), the canonical RAG bootstrap SOP from baseline `VectorStoreIndex` through hybrid + reranker + eval-loop hardening, the official 13-failure-mode checklist, and 5 dilemma cases distilled from docs, GitHub issues, and 2025 production post-mortems.
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。
Generate a coherent, whole-paper mathematical modeling solution framework from a complete contest problem. Use after the user supplies a CUMCM or other modeling problem and asks for modeling ideas, an overall solution plan, question-by-question analysis, candidate-model comparison, model-selection reasons, innovations, validation, or cross-question linkage. For every question, explain the task and mathematical essence, compare multiple feasible models in tables, recommend a route with explicit reasons, and keep all questions connected through shared data, variables, parameters, constraints, and 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。
Extract lessons from the current session, or sweep the project's past sessions when asked, and route them to the appropriate knowledge layer (project AGENTS.md, auto memory, existing skills, or new skills). Use when the user asks to "self-improve", "distill this session", "distill past sessions", "sweep past sessions", "extract lessons from all sessions", "save learnings", "update AGENTS.md with what we learned", "capture session insights", "remember this for next time", "extract lessons", "update skills from session", or "what did we learn".
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。
Extract lessons from the current session, or sweep the project's past sessions when asked, and route them to the appropriate knowledge layer (project AGENTS.md, auto memory, existing skills, or new skills). Use when the user asks to "self-improve", "distill this session", "distill past sessions", "sweep past sessions", "extract lessons from all sessions", "save learnings", "update CLAUDE.md with what we learned", "capture session insights", "remember this for next time", "extract lessons", "update skills from session", or "what did we learn".
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。
Analyze task complexity and route to a mode by artifact: direct fix for clear-scope changes, or a plan file when the approach needs to be written down. Use when the user asks to "turboplan", "run turboplan", "plan this task", "turbo plan mode", "plan and implement", or "use turboplan instead of plan mode".
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。
Adds HTTP endpoints in convex/http.ts: webhook receivers with signature checks, REST style routes, CORS, auth headers, streaming responses, and file uploads over HTTP. Use when integrating Stripe, Clerk, Resend, or any service that calls back into the app, or when a client needs a plain HTTP API.
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。
Routes Convex work to the right builder skill and covers the handful of rules that apply everywhere: validators on every function, withIndex over filter, idempotent mutations, internal functions for scheduling. Use when a task mentions Convex and no more specific skill matches, or as the first stop before picking one.
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。