「anthropic」の検索結果

Use when working on or testing imp-server and its HTTP APIs - OpenAI/Anthropic endpoints, /v1/chat/completions, /v1/messages, /v1/responses, SSE streaming, tool calling, json_schema/regex/GBNF constrained decoding, thinking/reasoning_content, cache_control/prefix cache, model loading and swapping, request priority, X-Request-Id, OTLP tracing / traceparent / Jaeger, /metrics, container env (IMP_SET), "server returns 404/garbage", API compliance. Do NOT use for CLI-only inference (imp-cli), kernel work (sm120-cuda-expert), or pure output-quality checks (check-degeneration).

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Shell out to Claude Code CLI to invoke a second Claude session headlessly. Useful for cross-validation, second opinions, and isolated analysis without sharing current agent context. Requires Anthropic account.

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Access the Anthropic product named Claude Design when the request contains that exact name, a claude.ai/design URL, or a .dc.html file. Also use for standalone-to-artifact migration and Claude Design artifact links. Use for projects, files, design systems, previews, conversations, comments, sharing, and code-to-design or design-to-code synchronization; otherwise stay inactive.

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Purpose: Guide creation of Claude Code agents following Anthropic official best practices.

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Best practices for designing Claude Code agent files (.claude/agents/*.md). This skill should be used when writing or reviewing agent markdown files to ensure proper design with focused domains, correct tool access, reusable definitions, and separation of capabilities from lifecycle. Combines Anthropic's official guidance with battle-tested patterns from agent team usage.

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Deploy, run, list, or tear down the agents in this repo's .managed-agents/ folder on Anthropic Managed Agents. Use when the user says "deploy my agents", "ship this agent to the cloud", "run the deployed agent", or asks about managed-agent deployment.

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Use when the user wants to be taught an Anthropic product or feature - "teach me Claude Code", "learn Cowork", "academy lesson", "train me on MCP or the Claude API", "quiz me", "next lesson" - or asks for structured learning rather than a one-off answer. Covers Claude Code, Claude.ai, Cowork, Tag, Platform/API, and AI Fluency. Do NOT use for auditing how the user already works (use academy-review) or for mid-task help where the user just wants their task done.

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OpenUI generative UI with LangChain/LangGraph backend. Supports ChatOpenAI and ChatAnthropic.

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OpenUI generative UI with Python FastAPI backend. OpenAI and Anthropic SDK variants.

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Assistant-behavior design skill for approximating a Claude-like analytical, careful, conversational style without claiming to be Claude or Anthropic. Use when the user asks to duplicate, emulate, adapt, or recreate a Claude-style "mythos" or persona for prompts, agent specs, writing style, reasoning discipline, safety posture, or UX behavior.

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Validate skills against Anthropic best practices for frontmatter, structure, content, file organization, hooks, MCP, and security (62 rules in 8 categories). Use when creating new skills, updating existing skills, before publishing skills, reviewing skill quality, or when user mentions "validate skill", "check skill", "skill best practices", "skill review", or "lint skill".

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Sync official Anthropic documentation and analyze impact on project components. Runs docs/reference/update-claude-docs.sh, computes diffs, and reports impacts on the skill validator, plugins, and project documentation. Use when user mentions "sync docs", "update reference docs", "refresh docs", or "check doc changes".

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Create or update Claude Code skills following Anthropic's official skill standard. Use when user says "create a skill", "new skill", "write a skill", "update a skill", "skill standard", or any time a new SKILL.md file needs to be created. Also use when reviewing existing skills for standards compliance.

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Use this skill when designing, generating an MVP blueprint for, auditing, troubleshooting, refactoring, or explaining an agentic harness for any domain. Covers provider-neutral agent architecture for OpenAI, Anthropic, and OpenAI-compatible APIs: agent loops, tool design, record provenance, interactive presentation, user-memory lifecycles, environment-adaptive tools, speculative tool execution, late-bound capabilities, permissions, system prompts, planning, goals, always-on agents and durable runtime, adaptive agent teams, context compaction, memory, skills, MCP/external connectors, public-board communications, hardware agents and board deployment, self-refining recursive harnesses, programmable context, continual refinement, observability, evals, prompt caching, agent-legible environments, feedback loops, and safety.

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Comprehensive MCP server development guide covering FastMCP 2.14.3 features, Anthropic standards, ecosystem integration, and production deployment across all agentic IDEs

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Guide for contributing new skills to the skills-x collection. This skill should be used when users want to add new open-source skills from external sources (like agentskills.io or anthropics/skills) to the skills-x repository. It covers the complete workflow from discovery to publishing.

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Schedule a moflo spell to run on the local machine via the moflo daemon (cron, interval, or one-time). Use when the user wants to schedule, automate, or recurringly run one of THEIR spells locally — e.g. "schedule the oap spell every hour", "run my audit spell every weekday at 9am", "fire X once tomorrow morning". This is the LOCAL daemon path. For remote Anthropic-cloud agents, use /schedule instead.

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Diagnose and test Claude Code skills against Anthropic's 7 principles. Scans SKILL.md files, checks 8 rules (gotchas, description, allowed-tools, file-size, structure, frontmatter, conflicts, usage-hooks), classifies skill types, generates prescriptions, and runs eval tests. Use when checking skill quality, auditing skills, testing skills, or before publishing skills. Triggers on "스킬 점검", "스킬 진단", "스킬 테스트", "check skills", "audit skills", "test skills", "skill health", "pulser", "pulser eval".

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GAN-inspired Generator-Evaluator agent harness for building high-quality applications autonomously. Based on Anthropic's March 2026 harness design paper.

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Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics. Based on Anthropic's Frontend Designer Skill

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为 OpenClaw 配置 MiniMax 作为模型源。MiniMax 提供两种接入方式：API Key 直连（openai-completions 协议）和 OAuth 门户（anthropic-messages 协议）。包含 provider 注册、模型定义、别名配置、fallback 链接入和验证的完整流程。当管理员说想"加 MiniMax"、"配 minimax"、"接入 MiniMax 模型"、"加海螺模型"、"配 M2.1"时使用此 skill。

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Launch Marcus multi-agent experiments with independent CLI agents in tmux panes. Use when the user says "build X with Marcus", "run a Marcus experiment", "spawn N agents with Marcus", "/marcus", or references the Marcus multi-agent framework. This skill handles experiment setup, config generation, and spawning independent agent CLI processes that coordinate via the Marcus MCP server. Each agent runs in its own tmux pane with full autonomy. NOT for ClawTeam — this is specifically for the Marcus MCP-based multi-agent system. NOTE: "Marcus" is also the name of the MCP server that agents use for coordination. The /marcus skill launches experiments that USE the Marcus MCP server — they are complementary, not competing. The MCP server must be running before invoking this skill. The Marcus MCP server is agent-agnostic; this skill supports Anthropic's claude CLI, OpenAI's codex CLI, and Google's gemini CLI as agent harnesses (selected via --harness).

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。

Launch Marcus multi-agent experiments with independent CLI agents in tmux panes. Use when the user says "build X with Marcus", "run a Marcus experiment", "spawn N agents with Marcus", "/marcus", or references the Marcus multi-agent framework. This skill handles experiment setup, config generation, and spawning independent agent CLI processes that coordinate via the Marcus MCP server. Each agent runs in its own tmux pane with full autonomy. NOT for ClawTeam — this is specifically for the Marcus MCP-based multi-agent system. NOTE: "Marcus" is also the name of the MCP server that agents use for coordination. The /marcus skill launches experiments that USE the Marcus MCP server — they are complementary, not competing. The MCP server must be running before invoking this skill. The Marcus MCP server is agent-agnostic; this skill supports both Anthropic's claude CLI and OpenAI's codex CLI as agent harnesses (selected via --harness).

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。

Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc. ) into focused tools people will pay for. Not just "ChatGPT but different" - products that solve specific problems with AI.

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。