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Automatically fix skill problems (safe preview first). Also use with --prune to find and remove broken symlinks, empty directories, and orphaned skills. Trigger with '/janitor-fix'.

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。

Heuristic security scan of installed skills — prompt-injection phrases, hidden unicode instructions, credential-store access, network-pipe-to-shell and payload-smuggling patterns. Use when the user asks 'are my skills safe', wants to scan skills for prompt injection or malware patterns, or before trusting a newly installed skill. Trigger with '/janitor-security'.

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。

Full health check of all your skills in one report. Use when the user wants to check for errors, find duplicates, detect broken skills, or get a complete overview of skill health. Pass --brief for inventory only. Trigger with '/janitor-report'.

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。

Fix bugs and broken behavior when there is enough evidence to act on a repair path. Use for errors, crashes, incorrect results, API failures (500, 404, 403), CORS problems, database exceptions, broken rendering, duplicated or wrong data, off-by-one mistakes, timezone/date bugs, broken forms, config-caused runtime failures, and regressions. Trigger when the user wants the bug repaired and the conversation already contains a clear failing area, a reproducible failing test, a concrete error path, or a prior diagnosis to implement. Do NOT use for new features, pure explanation, architecture discussion, broad research, or bug reports where the main need is figuring out why the behavior happens — use diagnose for that.

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。

Automated Planning utilities for loading PDDL domains and problems, generating plans using classical planners, validating plans, and saving plan outputs. Supports standard PDDL parsing, plan synthesis, and correctness verification.

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 GraphRAG retrieval pipelines on Neo4j using the neo4j-graphrag Python package (v1.22.0+). Covers retriever selection (VectorRetriever, HybridRetriever, VectorCypherRetriever, HybridCypherRetriever, Text2CypherRetriever, ToolsRetriever), external vector DB retrievers (Weaviate, Pinecone, Qdrant), retrieval_query Cypher fragments, query_params, filters, GraphRAG pipeline wiring (GraphRAG + LLM + prompt), all LLM providers (OpenAI, Anthropic, Gemini/VertexAI, Bedrock, Cohere, Mistral, Ollama), embedder setup, index creation, token usage tracking, Cypher 25 SEARCH clause, and LangChain/LlamaIndex integration. Does NOT handle KG construction — use neo4j-document-import-skill. Does NOT handle plain vector search — use neo4j-vector-index-skill. Does NOT handle GDS analytics — use neo4j-gds-skill. Does NOT handle agent memory — use neo4j-agent-memory-skill.

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。

Authoritative reference for the neo4j-agent-memory Python package — a graph-native memory system for AI agents built on Neo4j — and for the hosted service (NAMS) at memory.neo4jlabs.com. Use this skill whenever the user mentions neo4j-agent-memory, agent memory with Neo4j, context graphs, the POLE+O model, MemoryClient/MemorySettings, the memory MCP server, or any of the framework integrations (LangChain, PydanticAI, CrewAI, AWS Strands, Google ADK, Microsoft Agent Framework, OpenAI Agents, LlamaIndex). Also use when the user mentions the hosted service at memory.neo4jlabs.com, NAMS, the Neo4j Agent Memory Service, the `nams_` API key prefix, or the hosted MCP endpoint. Also use when writing documentation, blog posts, tutorials, PRDs, or code samples for the project, when comparing agent memory approaches, or when positioning graph-native memory against vector-only approaches — even if the user doesn't explicitly name the package.

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。

Ingests unstructured and semi-structured documents into Neo4j as a knowledge graph. Use when chunking PDFs, HTML, plain text, or Markdown; extracting entities and relationships from text with an LLM (SimpleKGPipeline, neo4j-graphrag); loading JSON via apoc.load.json; building Document→Chunk→Entity graph structures; or connecting LangChain/LlamaIndex document loaders to Neo4j. Covers neo4j-graphrag SimpleKGPipeline, LLM Graph Builder web UI, entity resolution, chunking strategies, and graph schema design for RAG pipelines. Does NOT handle structured CSV/relational import — use neo4j-import-skill. Does NOT handle GraphRAG retrieval after ingestion — use neo4j-graphrag-skill. Does NOT handle vector index creation — use neo4j-vector-search-skill.

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。

Save the currently active browser page to the link collection at saved.owenyoung.com. Use when explicitly invoked as $jj, or when the user asks to bookmark or collect the current page there. Read the page without navigating, generate a concise Chinese title, SEO slug, and distinctive Chinese Markdown description, attach the complete article or main-page text as Chinese-only Markdown, match collections, create one authenticated link record, and return its clickable URL.

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 diff adds or changes a loopback HTTP or WebSocket server, a bind address, a Unix socket, named pipe, XPC or D-Bus service, an Electron or Tauri main-process handler, a custom URL scheme or file association, a privileged helper or updater, or code that spawns tools inside directories a user or download supplied

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。

Maintain a dedicated automation test project per repository - separate from the product's unit tests - with API, worker, and UI suites written scenario-first

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 modelling a rich domain in Java - SOLID principles, encapsulated entities that enforce their own invariants, and value objects over primitives

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。

Guide for navigating and maintaining Kimix project documentation. Use when: (1) user asks about the docs structure, (2) user wants to add, update, or append content to project documents.

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。

Phase B of a WinForms-to-Avalonia migration: extract UI-independent application behavior, state rules, use cases, and boundary contracts with TDD and no WinForms/Avalonia references. Use only when an explicit migration still has business behavior in Forms or UI helpers, or when the orchestrator routes here. Do not build Avalonia XAML in this phase.

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。

Phase C of a WinForms-to-Avalonia migration: implement platform and infrastructure adapters for dependencies discovered in Phase A/B, such as persistence, process execution, dialogs, notifications, or environment capabilities. Use only in an explicit migration when such dependencies leak into Forms/core or when the orchestrator routes here. Do not invent adapters for capabilities the product does not have, and do not implement main-window XAML.

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 agent skills ecosystem to discover and install skills that extend AI coding agent capabilities. Use when user asks "how do I do X" (X being a common task), "find a skill for X", "is there a skill that can...", or expresses interest in extending agent capabilities. Triggers on "find a skill", "install a skill", "skill for [task]", "can you do X", "I need help with [domain]", "how do I [task]". Do NOT use when user has explicitly asked to proceed without a skill, or when the task is better handled by agent's built-in capabilities (file operations, git, basic coding).

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 senior software engineering standards when writing, editing, or refactoring any code. Use this skill whenever the user asks to write a function, build a feature, fix a bug, design a module, or improve existing code — even if they don't mention quality explicitly. The goal is production-grade code: readable, correct, maintainable, secure, and failure-aware. Always active for any coding task, at any scale.

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 skill for building, migrating, and maintaining Astro v7 projects. Covers best practices from the official AGENTS.md, the v6→v7 migration path, validation of breaking/deprecated patterns, AI-enhanced dev server usage (background mode, JSON logging), advanced routing with src/fetch.ts, route caching, Sätteri Markdown, and the Rust compiler. Use when the user mentions 'Astro', '.astro files', 'astro dev', 'astro build', 'islands architecture', 'content collections', 'SSG', 'SSR adapter', 'upgrade to Astro 7', 'migrate Astro', 'Astro v7', 'Astro v6', 'Sätteri', 'route caching', 'Astro.cache', 'astro dev --background', 'src/fetch.ts', 'advanced routing', 'Hono + Astro', 'Rolldown', 'Vite 8', 'queued rendering', 'CDN cache provider', 'Astro AI', 'related content', 'related posts', 'vector embeddings Astro', 'astro-related-content', or asks about static site generation with Astro.

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。

Creates FastAPI endpoints with layered architecture (Router → Service → Repository). Use when creating new API endpoints, CRUD operations, or scaffolding a new domain module in a FastAPI project.

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 the user asks about "code complexity", "cyclomatic complexity", "cognitive complexity", "code metrics", "maintainability index", "code coverage", or when measuring code quality quantitatively. Provides metrics thresholds and measurement techniques.

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。

Audit NFR evidence for performance, security, reliability, and maintainability. Use when implementation evidence exists and the user says "audit NFR evidence", "audit NFRs", or "evaluate non-functional requirements"

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。

SEO, AEO (Answer Engine Optimization), and GEO strategy for search engines and AI visibility. Use when working on "SEO audit," "technical SEO," "on-page SEO," "AI search optimization," "AEO," "GEO," "AI visibility," "optimize for ChatGPT," "optimize for Perplexity," "AI Overviews," "answer engine optimization," "generative engine optimization," "AI citations," "featured snippets," "meta tags," "schema markup," "search ranking," "content optimization," "E-E-A-T," "structured data," "search console," "SEO health check," "why am I not ranking," "AI search readiness," "backlink strategy," "link building," "domain authority," "programmatic SEO," "SEO at scale," "template-based SEO," "AEO monitoring," "AI search monitoring," "JSON-LD," "rich snippets," "schema.org," "SERP analysis," "search intent," "site architecture," "information architecture," "URL structure," "internal linking," or "navigation." For keyword research, see keyword-research-and-clustering.

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。

S6 of see-it-ship-it: put it at a public URL. Secret scan first; static builds go to GitHub Pages at no cost (sign-up guide, device-code login, one question: it will be public); a server only when a backend is needed, cost asked once; then open the URL, rerun the acceptance on the live page, bind a domain if they want 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。

Front-door router for the product-shots ecosystem. Clarifies underspecified visual creation requests through a 4-stage state machine, injects platform visual DNA (Amazon + 7 social platforms) and industry visual DNA (7 industries), enforces a unified Negative Constraints prompt patch, then routes to one of five downstream business skills (product-shots-main-image / product-shots-detail-page / product-shots-multi-angle / product-shots-ad-creative / product-shots-social-post). Use when the user says "I need a product image", "design something for my listing", "I need content for Instagram", "make an ad for me", "make a cover image", "create a post", "做一个商品图", "帮我做个详情页", "帮我做个广告图", "做一个社媒图", "做一张图", "帮我设计", "做个封面" — i.e. any underspecified visual creation request that needs clarification before generation. This is the intent-routing hub of the product-shots ecosystem.

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。