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Found 182 Skills
Build specialized openclaw agents with proper workspace structure, identity, and skills
Create new skills for the bench-skills repo following all conventions. Use when the user says "create a new skill", "add a skill", "new slash command", or wants to extend bench-skills with additional capabilities.
Build AI applications using Azure AI Projects SDK for JavaScript (@azure/ai-projects). Use when working with Foundry project clients, agents, connections, deployments, datasets, indexes, evaluations, or getting OpenAI clients.
This skill should be used when creating agents, writing agent frontmatter, configuring subagents, or when "create agent", "agent.md", "subagent", or "Task tool" are mentioned.
Example skill template. Replace this description with keywords and triggers for your actual skill. This description determines when the skill auto-loads based on conversation context.
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
Use when building custom Kiro AI agents or when user asks for agent configurations - provides JSON structure, tool configuration, prompt patterns, and security best practices for specialized development assistants
Epistemic verification framework for AI-generated assertions. Requires evidence before acting on LLM claims about code behavior, system state, API responses, or factual statements. Use when an AI agent makes claims that will drive decisions, before acting on research results, or when an agent asserts something is true without showing evidence.
Apply production-ready LangChain SDK patterns for chains, agents, and memory. Use when implementing LangChain integrations, refactoring code, or establishing team coding standards for LangChain applications. Trigger with phrases like "langchain SDK patterns", "langchain best practices", "langchain code patterns", "idiomatic langchain", "langchain architecture".
Initialize and configure LangGraph projects with proper structure, langgraph.json configuration, environment variables, and dependency management. Use when users want to (1) create a new LangGraph project, (2) set up langgraph.json for deployment, (3) configure environment variables for LLM providers, (4) initialize project structure for agents, (5) set up local development with LangGraph Studio, (6) configure dependencies (pyproject.toml, requirements.txt, package.json), or (7) troubleshoot project configuration issues.
Guide for creating and enhancing skills. Use when users want to create a new skill, update/improve an existing skill, or audit skill quality. Supports both creation from scratch and enhancement of existing skills with audit rubric scoring.
Build AI agents with persistent threads, tool calling, and streaming on Convex. Use when implementing chat interfaces, AI assistants, multi-agent workflows, RAG systems, or any LLM-powered features with message history.