alfworld-inventory-management
This skill tracks which objects have been collected and which remain to be found for multi-object tasks. It should be triggered when working with tasks requiring multiple instances of the same object type. The skill maintains a count of collected vs. needed objects and guides the search for remaining items.
alfworld-locate-target-object
This skill navigates to a suspected location and identifies a target object. It should be triggered when the agent's goal requires finding a specific object (e.g., 'potato', 'plate') and its location is not immediately known. The skill involves moving to a relevant receptacle (like a fridge or cabinet) and checking its contents, outputting the object's location or confirming its absence.
alfworld-location-navigator
Moves the agent to a specified receptacle or object location within the Alfworld environment. Use this skill when the agent needs to physically approach a target to inspect or interact with it, such as when checking an object's state or preparing for pickup. The skill takes a target location name as input and executes the 'go to' action, resulting in the agent being positioned at the destination for subsequent operations.
alfworld-object-cooler
This skill cools a held object using an appropriate cooling appliance, such as a fridge. It should be triggered when the task requires reducing the temperature of an object (e.g., a hot pot). The skill assumes the agent is holding the object and is near the cooling receptacle; it performs the 'cool' action to achieve the desired state change, preparing the object for subsequent steps like placement or serving.
alfworld-object-disposer
This skill disposes of an object by placing it into a disposal receptacle like a garbage can. It should be triggered when the task requires discarding an object (e.g., 'put it in garbagecan') and the agent is at the disposal location with the object in hand. The skill executes the 'put' action to place the object in/on the target receptacle, completing the disposal subtask.
alfworld-object-locator
This skill scans the current environment observation to identify the presence and location of a target object needed for a task. It should be triggered when the agent's goal requires an object that is not currently in the agent's inventory, and the observation does not explicitly state where the object is. The skill analyzes the textual observation to find receptacles that likely contain the target, based on common sense or domain knowledge (e.g., a 'dishsponge' might be on a 'cart'), and outputs the identified target receptacle location for navigation.
alfworld-object-picker
Picks up a specified object from a given receptacle. Use this skill when the agent has located a required object and needs to acquire it for later use, such as taking an item from a surface or container. The skill requires the object and source receptacle as inputs, executing a 'take' action to transfer the object into the agent's inventory, enabling further manipulation like placement or usage.
alfworld-object-state-inspector
Checks the current state or contents of a specified object or receptacle. Trigger this skill when the agent needs to determine if an object is present, missing, or in a certain condition before proceeding with a task, such as verifying if a holder is empty or if an item is available. It typically follows navigation and involves observing the environment's feedback, providing crucial information for decision-making in the task flow.
alfworld-object-state-modifier
This skill uses an appliance to change the state of an object (e.g., cooling, heating, cleaning). It should be triggered when the task requires altering an object's temperature or cleanliness using a specific device (like cooling with a fridge or heating with a microwave). The skill requires the object, the target state, and the appliance as inputs, and executes the corresponding modifier action (e.g., 'cool X with Y').
alfworld-object-storer
This skill places an object into a selected storage receptacle after confirming its suitability. It should be triggered when the agent has identified an appropriate storage location and is ready to complete the storage task. The skill takes the object and target receptacle as inputs and results in the object being stored.
alfworld-open-receptacle
This skill opens a closed receptacle to access its contents. It should be triggered when an agent needs to interact with items inside a closed container (e.g., fridge, microwave, drawer). The skill takes a receptacle identifier as input, performs the open action, and outputs the observation of the interior, enabling subsequent item retrieval or placement.
alfworld-tool-locator
This skill searches for a specified tool or device (e.g., a desklamp) within the environment by checking relevant surfaces. It should be triggered when the agent needs a tool to interact with another object as part of the task. The skill takes a tool name as implicit input and outputs navigation actions to likely storage spots (e.g., sidetables, shelves) until the tool is found.
align
Align skill for the ikigai project
allow-agent-commands
Add or change allowed commands in AI agent permission configs (OpenCode, Claude Code)
amq-cli
>-
claude-agent-sdk
This skill should be used when building applications with the Claude Agent SDK (Python). Use for creating orchestrators with subagents, configuring agents programmatically, setting up hooks and permissions, and following SDK best practices. Trigger when implementing agentic workflows, multi-agent systems, or SDK-based automation.
PheroPath
A filesystem-based stigmergy communication protocol. Use this to leave invisible "pheromones" (signals) on files to communicate context, risks, or status to other agents or your future self without modifying file content.
scope
Hard-block edits outside declared frozen directories via PreToolUse hook.
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.
abductive-repl
Hypothesis-Test Loops via REPL for Exploratory Abductive Inference with Gay.jl colors
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.
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.
agent-ai-engineer
Expert AI engineer specializing in AI system design, model implementation, and production deployment. Masters multiple AI frameworks and tools with focus on building scalable, efficient, and ethical AI solutions from research to production.
agent-bricks
Create and manage Databricks Agent Bricks: Knowledge Assistants (KA) for document Q&A, Genie Spaces for SQL exploration, and Multi-Agent Supervisors (MAS) for multi-agent orchestration. Use when building conversational AI applications on Databricks.
agent-cost-optimizer
Real-time cost tracking, budget enforcement, and ROI measurement for AI agent operations. Track token usage, predict costs, enforce budget caps ($50-70/month typical), optimize model selection, cache results, measure cost-to-value. Use when tracking AI costs, preventing budget overruns, optimizing spend, measuring ROI, or ensuring cost-effective AI operations.
agent-evals
Design and implement evaluation frameworks for AI agents. Use when testing agent reasoning quality, building graders, doing error analysis, or establishing regression protection. Framework-agnostic concepts that apply to any SDK.
agent-llm-architect
Expert LLM architect specializing in large language model architecture, deployment, and optimization. Masters LLM system design, fine-tuning strategies, and production serving with focus on building scalable, efficient, and safe LLM applications.
agent-o-rama
Layer 4: Learning and Pattern Extraction for Cognitive Surrogate Systems
agent-sdk
Expert in Claude Agent SDK development. Use when users ask about SDK API, agent configuration, MCP servers, hooks, permissions, file checkpointing, or when they mention @AGENT_SDK_DOCS.md. Provides accurate API reference, code examples with TypeScript types, and best practices.
agent-sdk-development
Central authority for Claude Agent SDK (TypeScript and Python SDKs). Covers SDK installation, authentication (Anthropic key, Bedrock, Vertex), sessions and resumption, forking sessions, streaming vs single mode, custom tools, permissions (allowedTools, disallowedTools, permissionMode), MCP integration, system prompts (CLAUDE.md, appendSystemPrompt, outputStyle), cost tracking, todo tracking, structured outputs, hosting patterns, plugins, and SDK branding guidelines. Assists with building custom agents, configuring SDK options, and troubleshooting SDK issues. Delegates 100% to docs-management skill for official documentation.
agent-selecting-models
Guidance for selecting appropriate AI model (sonnet vs haiku) based on task complexity, reasoning requirements, and performance needs. Use when implementing agents or justifying model selection.
agent-tools
Run 150+ AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating images/videos, calling LLMs, web search, or automating Twitter. Triggers: inference.sh, infsh, ai model, run ai, serverless ai, ai api, flux, veo, claude api, image generation, video generation, openrouter, tavily, exa search, twitter api, grok
AgentDB Learning Plugins
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
AgentDB Memory Patterns
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.
AgentDB Vector Search
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.
agentic-eval
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agentskb
AgentsKB - Knowledge Base API for AI Agents with 32K+ technical Q&As
ai-analysis
>
ai-apis-like-chatgpt
How to use AI APIs like OpenAI, ChatGPT, Elevenlabs, etc. When a user asks you to make an app that requires an AI API, use this skill to understand how to use the API or how to respond to the user.
ai-assistants
AI-powered development tools configuration and usage
ai-assisted-operations
AI-powered issue operations via gh-models. TRIGGERS - issue summarization, auto-labeling, issue insights.
ai-consultation
Provides AI consultation workflows, prompt templates, and best practices for multi-model consultation. Use when user asks for "second opinion", "ask codex", "ask gemini", "AI code review", "external AI consultation", or needs prompt templates for code review, security audit, or architecture analysis.
ai-context-optimizer
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ai-engineer-agent
Build LLM applications, RAG systems, and prompt pipelines. Implements vector search, agent orchestration, and AI API integrations. Use when building LLM features, chatbots, AI-powered applications, or need guidance on AI/ML engineering patterns.
ai-engineer-expert
Expert-level AI implementation, deployment, LLM integration, and production AI systems
ai-ethics
Responsible AI development and ethical considerations. Use when evaluating
ai-eval-design-and-iteration
Develop "quizzes" (evals) to measure model performance on specific tasks. Use these benchmarks to guide fine-tuning, determine product UX patterns, and track performance improvements over time. Use this when launching a new AI feature, switching between model versions, or optimizing for high-stakes accuracy.
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