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Found 493 Skills
Evaluates agent skills against Anthropic's best practices. Use when asked to review, evaluate, assess, or audit a skill for quality. Analyzes SKILL.md structure, naming conventions, description quality, content organization, and identifies anti-patterns. Produces actionable improvement recommendations.
Use when working with Anthropic Claude Agent SDK. Provides architecture guidance, implementation patterns, best practices, and common pitfalls.
Coaches behavioral and values-fit interview preparation with negative framing, deep follow-ups, introspection, and mission alignment. Use for culture-fit rounds, Anthropic behavioral prep, failure stories, and self-awareness drilling. Activate on "behavioral interview", "values interview", "culture fit", "tell me about a failure". NOT for coding interviews, system design, resume writing, or technical deep dives.
Comprehensive guide for creating Claude Code agents with proper structure, triggering conditions, system prompts, and validation - combines official Anthropic best practices with proven patterns
添加和配置第三方 API 中转站供应商到 OpenClaw。当用户需要添加新的 API 供应商、配置中转站、设置自定义模型端点时使用此技能。支持 Anthropic 兼容和 OpenAI 兼容的 API 格式。
Evaluates agent skills against Anthropic's best practices. Use when asked to review, evaluate, assess, or audit a skill for quality. Analyzes SKILL.md structure, naming conventions, description quality, content organization, and identifies anti-patterns. Produces actionable improvement recommendations.
CLAUDE.md file generation and optimization for Claude Code projects. Capabilities: initialize project instructions, analyze codebase context, optimize existing CLAUDE.md, apply Anthropic best practices, reduce token usage, improve effectiveness. Actions: init, create, optimize, enhance CLAUDE.md files. Keywords: CLAUDE.md, project instructions, Claude Code setup, project context, codebase analysis, Anthropic best practices, token optimization, project configuration, AI instructions, coding guidelines, project rules, workspace setup. Use when: initializing CLAUDE.md for new projects, optimizing existing project instructions, setting up Claude Code for a codebase, improving AI coding guidelines.
Audits and auto-fixes a project's CLAUDE.md against Anthropic best practices. Activates during ship phase — checks conciseness, enforces @import structure for detailed docs, auto-excludes bloat, identifies hook candidates, and auto-fixes structural issues. Flags content questions for developer review.
Creates and configures Claude Code hooks for lifecycle automation. Covers all 17 hook events, 4 hook types (command, prompt, agent, http), matchers, input/output formats, and exit codes. Follows official Anthropic best practices. USE WHEN: user mentions "hook", "hooks", "auto-format", "pre tool use", "post tool use", "session start", "notification hook", "block command", "validate tool", "lifecycle event", "PostToolUse", "PreToolUse" DO NOT USE FOR: creating skills - use `skill-authoring`; creating agents - use `agent-authoring`; webhook endpoints - different concept
Mine Gmail history into a local flat-file knowledge base (~/.cortex/). Use when asked to "run the cortex", "mine emails", "cortex run", "cortex dry run", "set up the cortex", "cortex from DATE", or "mine my inbox". Extracts contacts, clients, communications and knowledge facts into portable JSONL/JSON files. Requires gws CLI and ANTHROPIC_API_KEY.
Meta-skill for improving and optimizing prompts using Anthropic's prompt engineering best practices. Provides the 4-step improvement workflow (example identification, initial draft, chain of thought refinement, example enhancement), keyword registries for documentation lookup, and decision trees for improvement strategies. Use when improving prompts, optimizing for accuracy, adding chain of thought reasoning, structuring with XML tags, enhancing examples, or iterating on prompt quality. Delegates to docs-management skill for official prompt engineering documentation.
Use when optimizing CLAUDE.md, AGENTS.md, custom commands, or skill files for Claude 4.5 models - applies documented Anthropic best practices systematically instead of inventing improvements