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Found 1,197 Skills
Provides tool and function calling patterns with LangChain4j. Handles defining tools, function calls, and LLM agent integration. Use when building agentic applications that interact with tools.
OPC Architecture Understanding
Guidelines to create/update a new mode for PostHog AI agent. Modes are a way to limit what tools, prompts, and prompt injections are applied and under what conditions. Achieve better results using your plan mode.
Configure OpenClaw gateway integration for waking external automations and AI agents on hook events
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
Prepare branch for code review by building context, identifying issues, and suggesting improvements
This skill should be used when the user requests to "initialize team", "create development team", "team init", "form a team", or "start project team". It collects project information through interactive Q&A and creates an Agent engineering team with professional roles. 8 team types are supported: software development, software testing, reverse engineering, debugging/bug fixing, security research, CTF competition, software and server operation & maintenance, discussion/seminar.
OpenClaw-RL framework for training personalized AI agents via reinforcement learning from natural conversation feedback
Installs or updates Codex CLI, Gemini CLI, and Claude Code. Use when CLI agents need installation or update.
Agent skill for code-review-swarm - invoke with $agent-code-review-swarm
Aggregate and rank signals from multiple edge-finding skills (edge-candidate-agent, theme-detector, sector-analyst, institutional-flow-tracker) into a prioritized conviction dashboard with weighted scoring, deduplication, and contradiction detection.
Mandatory protocol for dispatching any built-in and custom agent in this project via the task tool. Use this skill EVERY TIME you are about to call the task tool with a custom agent_type. This skill ensures the agent's intended model (declared in its YAML frontmatter) is respected rather than overridden by a default. Also encodes prompting best practices for subagent context and quality. ALWAYS invoke before any task tool call that targets a custom agent — even if the agent name seems obvious.