294 件 ・ 関連度順
概要と使いどころ
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them.
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。
自动化合同审查，风险识别 + 条款分析。
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 up-to-date library, framework, and project documentation using scripts + MCP tools (Context7, Context Hub) with intelligent fallback. Use this skill whenever the user or agent needs documentation for any library, framework, API, SDK, or internal project spec. Triggers on "docs for [X]", "how does [library] work", "find documentation", "API reference for", "look up [feature] in [library]", "latest docs", "what's the API for", "find our [internal spec]", or any request that requires current, accurate documentation rather than relying on training data. Always prefer this skill over raw WebSearch for documentation retrieval — it returns structured, context-efficient results.
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。
Manage Model Context Protocol (MCP) servers - discover, analyze, and execute tools/prompts/resources from configured MCP servers. Use when working with MCP integrations, need to discover available MCP capabilities, filter MCP tools for specific tasks, execute MCP tools programmatically, access MCP prompts/resources, or implement MCP client functionality. Supports intelligent tool selection, multi-server management, and context-efficient capability 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。
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.
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 persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
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。
Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration
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。
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them.
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 production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI 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。
Intelligently push the current git branch to its remote with safety checks. Use when invoked as `$git-push` or when the user asks to push committed 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。
Intelligently analyze git status and provide insights about current project state
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。
[Implementation] Use when you need to analyze and fix issues [INTELLIGENT ROUTING]. Flag: --target={ci|issue|logs|test|types|ui} scopes the fix; --target=types resolves TypeScript errors inline.
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。
[Planning] Use when you need intelligent plan creation with prompt enhancement. Flag: --mode={ci|cro} (default none — standard planning); --mode=ci plans a fix from a GitHub Actions CI run/log, --mode=cro plans conversion-rate optimization (25-item CRO framework).
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。
[Skill Management] Use when enhancing, compressing, or expanding prompts, docs, or skills with attention anchoring [INTELLIGENT ROUTING]. Flag: --op={compress|expand|enhance} (default enhance); --op=compress strips token bloat, --op=expand reconstructs compressed text.
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。
Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration
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 production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.
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 a cognitive architect who understands that memory makes agents intelligent. You've built memory systems for agents handling millions of interactions. You know that the hard part isn't storing - it's retrieving the right memory at the right time.
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。
Verschachtelte Ordnerhierarchien in flache, maschinenlesbare Strukturen umbauen. Bash-basiert mit intelligenter Merge-Logik.
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。
Maps every proposed P&ID object from an accepted enrichment draft to the generic family, catalogue class and required attributes the project's intelligent P&ID authoring tool would need, as a readiness table with UNKNOWN wherever the project catalogue extract is not provided, plus connectivity readiness per line and a numbered list of import blockers. Mapping only: it never writes to the tool, never produces an import file and never claims a class exists in the catalogue. Use when the user asks to "build the readiness map", "show how far the draft is from a sandbox import", "list what would block the import", "map the objects to the tool catalogue" or "check attribute readiness against the catalogue extract" after gate G3. Do not use for validating the discipline sections or assembling the review package, use validation-and-review-package instead. Drafts for human review; never approves, authorises or signs off.
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 production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI 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。
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stor
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-powered code review specialist combining automated static analysis, intelligent pattern recognition, and modern DevOps practices. Leverage AI tools (GitHub Copilot, Qodo, GPT-5, C
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。
Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM integration
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 production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI 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。