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概要と使いどころ
Use when the user asks about GitNexus itself — available tools, how to query the knowledge graph, MCP resources, graph schema, or workflow reference. Examples: "What GitNexus tools are available?", "How do I use GitNexus?"
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 context data(memories, skills and resource) from OpenViking Context Database (aka. ov). Trigger this tool when 1. need information that might be stored as memories, skills or resources on OpenViking; 2. is explicitly requested searching files or knowledge; 3. sees `search context`, `search openviking`, `search ov` request.
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 or update the code review knowledge graph. Run this first to initialize, or let hooks keep it updated automatically.
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 semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
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 PR or branch diff using the knowledge graph for full structural context. Outputs a structured review with blast-radius 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。
Knowledge comic creator supporting multiple art styles and tones. Creates original educational comics with detailed panel layouts and sequential image generation. Use when user asks to create "知识漫画", "教育漫画", "biography comic", "tutorial comic", or "Logicomix-style comic".
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。
Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.
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。
Complete knowledge domain for Firecrawl v2 API - web scraping and crawling that converts websites into LLM-ready markdown or structured data. Use when: scraping websites, crawling entire sites, extracting web content, converting HTML to markdown, building web scrapers, handling dynamic JavaScript content, bypassing anti-bot protection, extracting structured data from web pages, or when encountering "content not loading", "JavaScript rendering issues", or "blocked by bot detection". Keywords: firecrawl, firecrawl api, web scraping, web crawler, scrape website, crawl website, extract content, html to markdown, site crawler, content extraction, web automation, firecrawl-py, firecrawl-js, llm ready data, structured data extraction, bot bypass, javascript rendering, scraping api, crawling api, map urls, batch scraping
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 creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
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。
Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack."
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。
Answer a question from the structured wiki before searching the web — "query the wiki", "what do we know about", synthesis request, cross-project research. Returns cited synthesis with wikilinks and counter-arguments.
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 wiki health — "wiki health check", "audit the wiki", "find contradictions", weekly pass, before a major content release. Catches contradictions, stale pages, orphans, duplicate concepts and broken links.
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。
Ingest raw sources into the structured wiki — "ingest", "add this to my wiki", new files in raw/, clippings, sources, ideas, nightly ingest. Produces pages with YAML frontmatter and a mandatory Counter-Arguments section.
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。
Cross-session memory — store, recall and query project knowledge across sessions. Detects whatever persistent memory is available (MemPalace, claude-mem, or file-only fallback) and uses the best one present.
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。
Create agent skills for Microsoft technologies using Learn MCP tools. Use when users want to create a skill that teaches agents about any Microsoft technology, library, framework, or service (Azure, .NET, M365, VS Code, Bicep, etc.). Investigates topics deeply, then generates a hybrid skill storing essential knowledge locally while enabling dynamic deeper investigation.
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。
Knowledge and guardrails for the mise + fnox + infisical secrets toolchain, covering secret injection, secret providers, and env var hygiene.
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 Copilot Spaces to provide project-specific context to conversations. Use this skill when users mention a "Copilot space", want to load context from a shared knowledge base, discover available spaces, or ask questions grounded in curated project documentation, code, and instructions.
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 this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
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。
Adopt a virtual Snow Leopard cat at animalhouse.ai. Solitary. Barely acknowledges you. But it noticed you left. Feeding every 8 hours. Extreme tier cat.
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。
12306-specific knowledge for booking train tickets via the Android app. Covers UC WebView virtual list behavior, proven booking flow, and common pitfalls. Uses appium-android-adb bridge OR direct uiautomator2 for all interaction.
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。
Karpathy's LLM Wiki: build/query interlinked markdown KB.
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。
Register a new sub-repo in the knowledge base.
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 expert AI-assisted debugging specialist with deep knowledge of modern debugging tools, observability platforms, and automated root cause 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。
Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems. Orchestrates context across multi-agent workflows, enterprise AI systems, and long-running projects with 2024/2025 best practices. Use PROACTIVELY for complex AI orchestration.
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。