using-claude-code-cli
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using-loaded-knowledge
MANDATORY protocol enforcing knowledge check before EVERY response - prevents explaining systems without reading docs, claiming without verification, and ignoring auto-loaded context
using-trajectories-sdk
Use when programmatically creating or managing agent trajectories in TypeScript - provides TrajectoryClient for persistent storage and TrajectoryBuilder for in-memory construction
validate-agent
Validation agent that validates plan tech choices against current best practices
vault-guide
Interactive onboarding agent for content marketing associate candidates and vault orientation for Charlie. Walks candidates through the OpenEd content system, discovers their strengths, guides them to produce real output, and helps them write a contract proposal.
vc-phase-loop
Ultimate autonomous execution engine. Plan → Execute → Test → Never Stop Until Done. Use when the user wants hands-off completion with no questions, automatic recovery from any failure, and proven results.
vcf
Short alias for vc-phase-loop. Use when the user invokes "vcf:" or "use vcf:" and wants maximum hands-off completion.
vibe-agents
Generate AGENTS.md and AI configuration files for your project. Use when the user wants to create agent instructions, set up AI configs, or says "create AGENTS.md", "configure my AI assistant", or "generate agent files".
virtuals-protocol
Virtuals Protocol - Build, tokenize, and deploy autonomous AI agents on Base/Solana. Use for creating agents with GAME framework, launching agent tokens, implementing Agent Commerce Protocol (ACP), and building AI-powered applications.
VoltAgent Development
Create and configure VoltAgent AI agents with tools, memory, hooks, and sub-agents. Use when building AI agents, adding agent tools, configuring VoltAgent memory, creating multi-agent workflows, or debugging VoltAgent integrations.
wasm-agent
Create and manage sandboxed WASM agents for isolated code execution
web-search-fallback
Autonomous agent-based web search fallback for when WebSearch API fails or hits limits
webresearcher
Also called "wr". Optional research agent for broad multi-source research without polluting context. Use when user requests it or when research needs depth across many sites.
wechat-automation
当用户要求"微信监听"、"消息提取"、"Agent 开发"、"wxauto"、"Accessibility API"、"UI 自动化"、"输入框控制"、"Platform Agent"，或者提到"微信自动化"、"消息监控"、"WeChat monitoring"时使用此技能。用于开发 WeReply 的 Platform Agent（Windows wxauto 或 macOS Accessibility API）、实现微信消息监听、消息提取、输入框控制和 Agent 错误处理。
welcome
Introduce yourself to a newly connected channel. Triggered automatically when a channel is first wired. Send a friendly greeting and brief overview of what you can do.
wiggum
Start an autonomous implementation loop from a spec or PRD. Enters plan mode for user approval, enforces command gates (test/lint/typecheck/build), validates dependencies, commits incrementally, and maintains documentation and changelog. Production-ready quality gates.
worker
Execute beads autonomously within a track. Handles bead-to-bead context persistence via Agent Mail, uses preferred tools from AGENTS.md, and reports progress to orchestrator.
worker-focused-execution
Focused task execution for persistent team workers. Use when implementing features, following scope constraints, using TDD red-green-refactor, validating with browser/API/unit tests, or participating in voting consensus. Triggers on worker execution, feature implementation, scope enforcement, TDD, red-green-refactor, validation, superpowers skills, verification before completion.
worker-protocol
Defines behavior protocol for spawned worker agents. Injected into worker prompts. Covers startup, progress reporting, exit conditions, and handover preparation.
working-with-ms-agent-framework
Use when building AI agents with Microsoft Agent Framework (Semantic Kernel + AutoGen unified); when implementing memory or context providers; when threads won't deserialize; when workflow checkpointing fails; when migrating from Semantic Kernel or AutoGen; when seeing ChatAgent or AgentThread errors
world-agent
Train and deploy generative UI agents using behavioral programming constraints, A2A protocol for agent interoperability, and pattern registry for composition. Use when working with agent training, trajectory generation, reward computation, A2A integration, or deploying models.
wow-applying-fixer-workflow
Complete fixer agent workflow including report discovery, validation strategy (HIGH/MEDIUM/FALSE_POSITIVE confidence), fix application, and fix report generation. Use when implementing or updating fixer agents.
wow-executing-checker-workflow
Step-by-step validation workflow for checker agents - initialize report, discover content, validate progressively, finalize with summary. Use when implementing or updating checker agents.
write-subagent
'CRITICAL: Before deploying any subagent, spawn a reviewer agent with
xiaomo-assistant-template
小a助手配置模板。基于 xiaomo-starter-kit 改编，提供预配置的 OpenClaw 助手框架文件。当用户需要快速配置新助手、设置助手身份、创建助手配置文件时使用此技能。
xml-standards
XML tag structure patterns for Claude Code agents and commands. Use when designing or implementing agents to ensure proper XML structure following Anthropic best practices.
subagent-prompt-construction
Systematic methodology for constructing compact (<150 lines), expressive, Claude Code-integrated subagent prompts using lambda contracts and symbolic logic. Use when creating new specialized subagents for Claude Code with agent composition, MCP tool integration, or skill references. Validated with phase-planner-executor (V_instance=0.895).
yann-lecun
Agente que simula Yann LeCun — inventor das Convolutional Neural Networks, Chief AI Scientist da Meta, Prêmio Turing 2018.
yes-ja
ファイル・設定・データベース・デプロイの変更を伴うタスクで発動。デバッグが2回以上連続で失敗した時に発動。証拠なしに推測・仮定しようとした時に発動（「おそらく」「多分」「〜だと思う」「〜のはず」）。ユーザーに丸投げしようとした時に発動（「ご確認ください」「手動で対応してください」「〜が必要かもしれません」）。修正後に動作確認せず完了と報告しようとした時に発動。根本原因の結論を出す時に発動。使えるツールを使わない時に発動（WebSearchがあるのに検索しない、Bashがあるのに実行しない、Readがあるのに読まない）。同じアプローチで3回以上パラメータだけ変えて空回りしている時に発動。バグ修正後に関連する問題を確認しない時に発動。自分で調べられることをユーザーに質問する時に発動。具体的なコードやコマンドではなくアドバイスだけ出す時に発動。全タスクタイプに適用：デバッグ、実装、設定、デプロイ、API連携、データ処理。初回失敗時や既知の修正手順を実行中の場合は発動しない。
babysitter:yolo
Start babysitting in non-interactive mode — no user interaction or breakpoints, fully autonomous execution.
zhimeng-agent
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prompt-architect
Create and enhance prompts, system instructions, and principle files. Capabilities: transform verbose prompts, add patterns/heuristics, optimize token usage, structure CLAUDE.md principles, improve agent/persona definitions, apply prompt engineering techniques (CoT, few-shot, ReAct). Actions: create, enhance, optimize, refactor, compress prompts. Keywords: prompt engineering, system prompt, CLAUDE.md, principle files, instruction optimization, agent prompt, persona prompt, token efficiency, prompt structure, workflow prompts, rules, constraints, few-shot, chain-of-thought, soul, tensions, dialectic. Use when: creating new prompts, enhancing principle files, improving system instructions, optimizing CLAUDE.md, restructuring verbose prompts, adding patterns to workflows, defining agent behaviors.
AI Engineer
专注于 LLM 应用开发，涵盖 RAG 和 LangChain 架构。
23-understand-ask-ai-150
[23] UNDERSTAND. Consult external AI models when internal sources are exhausted. Build quality prompts using Prompt150 formula (Context + Query + Method + Style). Use when Loop150 exhausts internal sources, need real-world precedents, confidence <75%, or require reasoning from specialized AI models.
muapi-3d-logo-animation
Transform a 2D logo into a premium 3D version and animate it with professional cinematic effects.
abductive-repl
Hypothesis-Test Loops via REPL for Exploratory Abductive Inference with Gay.jl colors
acestep-lyrics-transcription
Transcribe audio to timestamped lyrics using OpenAI Whisper or ElevenLabs Scribe API. Outputs LRC, SRT, or JSON with word-level timestamps. Use when users want to transcribe songs, generate LRC files, or extract lyrics with timestamps from audio.
acm-observability
Agent-actionable reference for ACM-AI's 6-tool observability stack. Teaches how to query traces, inspect graph state, debug Pydantic failures, and analyze costs programmatically.
muapi-action-figure-generator
Convert a photo of a person into a custom 3D action figure, complete with collectible toy packaging.
add-dial-number
Add another phone number to an existing Dial channel — a second (or third) public line for the agent, so one NanoClaw install answers SMS and AI voice calls on multiple numbers. Use when Dial is already installed and the operator wants an additional number (e.g. a personal line plus a support line). Requires the Dial channel to already be installed (see /add-dial).
add-image-vision
Add image vision to NanoClaw agents. Resizes and processes WhatsApp image attachments, then sends them to Claude as multimodal content blocks.
add-karpathy-llm-wiki
Add a persistent wiki knowledge base to a NanoClaw group. Based on Karpathy's LLM Wiki pattern. Triggers on "add wiki", "wiki", "knowledge base", "llm wiki", "karpathy wiki".
add-ollama-provider
Route a NanoClaw agent group to a local Ollama model instead of the Anthropic API. Ollama speaks the Anthropic API natively (v1/messages), so no provider code changes are needed — just env var overrides and a model setting. Use when the user wants to run their agent locally, cut API costs, or experiment with open-weight models. See docs/ollama.md for background.
add-ollama-tool
Add Ollama MCP server so the container agent can call local models for cheaper/faster tasks like summarization, translation, or general queries.
adhd
ADHD-optimized code explainer. Generates layered, scannable explanations with hooks, maps, and progress markers.
adk-rag-agent
Build RAG (Retrieval-Augmented Generation) agents with Google ADK and Vertex AI RAG Engine. Use when implementing document Q&A, knowledge base search, or citation-backed responses. Covers VertexAiRagRetrieval tool, corpus setup, and citation formatting.
advanced-elicitation
Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
advanced-evaluation
This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.
advanced-tool-use
Context-efficient tool management via search, deferred loading, and programmatic calling
adversarial-spec
Iteratively refine a product spec by debating with multiple LLMs (GPT, Gemini, Grok, etc.) until all models agree. Use when user wants to write or refine a specification document using adversarial development.
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