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概要と使いどころ
Create, redesign, repair, validate, preview, and package lightweight standalone HTML deliverables. Use for marketing experiences, product prototypes, infographics, motion narratives, documents, browser tools, dashboards, guided workflows, knowledge interfaces, mini-games, presentations, reusable style and brand systems, and local-model text, vision, image, or code tools that must run without a build chain or hosted service.
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 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。
Configure the project's game engine and version. Pins the engine in AGENTS.md, detects knowledge gaps, and populates engine reference docs via webfetch when the version is beyond the LLM's training data.
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。
Guided, section-by-section authoring of the master architecture document for the game. Reads all GDDs, the systems index, existing ADRs, and the engine reference library to produce a complete architecture blueprint before any code is written. Engine-version-aware: flags knowledge gaps and validates decisions against the pinned engine version.
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。
Stop and consult this skill whenever your response would include specific facts about Anthropic's products. Covers: Claude Code (how to install, Node.js requirements, platform/OS support, MCP server integration, configuration), Claude API (function calling/tool use, batch processing, SDK usage, rate limits, pricing, models, streaming), and Claude.ai (Pro vs Team vs Enterprise plans, feature limits). Trigger this even for coding tasks that use the Anthropic SDK, content creation mentioning Claude capabilities or pricing, or LLM provider comparisons. Any time you would otherwise rely on memory for Anthropic product details, verify here instead — your training data may be outdated or wrong.
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。
Use this skill when the user's prompt requires (1) researching a topic across multiple sources, comparing options or alternatives, analyzing trends or history, understanding markets or industries, or reviewing literature or studies and (2) synthesizing that research into a comprehensive, narrative report. If you're planning to search the web or internal knowledge bases, consider using this skill. This skill coordinates research subagents, so use it only when you have a tool for spawning subagents (the Agent or Task tool); otherwise, research the question 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。
Save and recall durable knowledge through octop-memory; distinguish user-maintained MEMORY.md from workspace configuration.
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 the harness memory files (USER.md, MEMORY.md, AGENTS.md) so that long-term knowledge persists across conversations.
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。
Retrieve relevant memories for the current task from AgentDB. Use at the start of a task to load prior knowledge, when stuck to surface what worked before, or when the user asks "what do we know about X" / "have we done this before?"
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。
Converting technical knowledge into durable learning documents and publishable articles. Use for diff-based teaching, decision records, onboarding, note/Zenn/Qiita/dev.to posts, article series, retrospectives, and cross-platform repurposing.
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。
Refracting thinking by challenging assumptions, combining cross-domain knowledge, and shifting perspectives to reframe problems. Use for stuck situations or paradigm shifts. Does not write code.
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。
Orchestrating ecosystem self-evolution: lifecycle-phase detection, agent relevance, cross-agent knowledge synthesis, evolution proposals. Use when auditing skill-ecosystem health or fitness.
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, query, and inspect the project knowledge graph in .planning/graphs/
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 a scope and sequence showing vertical and horizontal curriculum coherence across a programme or year. Use when building new programmes, restructuring subjects, or ensuring progression.
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。
Author learning targets for a competency across developmental bands with precise, observable progression language. Use when writing 'I can' statements for competency-based programmes.
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。
Synthesise completed KUD charts into a developmental progression matrix and per-competency narrative sections. Use when you need a programme-level view of how knowledge, understanding, and performance develop across bands.
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 a Funhouse Mirror activity where students use their own domain expertise to detect AI distortions, omissions, and overconfidence. Use when students know a subject well enough to evaluate AI claims about it.
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。
Redesign a lesson to centre students' cultural backgrounds, community knowledge, and lived experience. Use when making curriculum relevant and inclusive for diverse student populations.
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。
When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured data," "JSON-LD," "rich snippets," "schema.org," "FAQ schema," "product schema," "review schema," "breadcrumb schema," "Google rich results," "knowledge panel," "star ratings in search," or "add structured data." Use this whenever someone wants their pages to show enhanced results in Google. For broader SEO issues, see seo-audit. For AI search optimization, see ai-seo.
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。
RAG & Knowledge Architect: Retrieval systems: ingestion, chunking, embeddings, hybrid search, reranking, evals.
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。
Technical documentation specialist and knowledge curator. Use when the user asks to talk to Paige or requests the tech writer.
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 accurate, runnable quantitative strategy code for the JoinQuant (聚宽) platform. Use this skill when the user asks to write a stock/ETF/futures backtest, paper-trading, or live-trading strategy on JoinQuant — the skill provides progressive-disclosure access to the complete JoinQuant API knowledge base (14 categories, 294KB official docs), 5 production-ready strategy templates (single-stock MA, multi-factor, ETF rotation, momentum, mean-reversion), and a lint tool that catches hallucinated APIs, future-function violations, and unset price-mode/slippage/commission. Chinese-friendly. Code generated by this skill should paste directly into the JoinQuant online editor without modification.
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。