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Found 7,140 Skills
Master Map of Content (MOC) for the GDSkills library. This skill acts as a central index and discovery hub for all 80+ Godot-focused agentic skills. Use this to identify relevant skills for architecture, 2D/3D systems, gameplay mechanics, and optimization. Trigger keywords: MOC, index, table of contents, library map, skill discovery, Godot skills list.
Patterns and architectures for building AI agents and workflows with LLMs. Use when designing systems that involve tool use, multi-step reasoning, autonomous decision-making, or orchestration of LLM-driven tasks.
Configure AI coding agents to be honest, objective, and non-sycophantic. Use when the user wants to set up honest feedback, disable people-pleasing behavior, enable objective criticism, or configure agents to contradict when needed. Triggers on honest agent, objective feedback, no sycophancy, honest criticism, contradict me, challenge assumptions, honest mode, brutal honesty.
Use when receiving code review feedback (especially if unclear or technically questionable), when completing tasks or major features requiring review before proceeding, or before making any completion/success claims. Covers three practices - receiving feedback with technical rigor over performative agreement, requesting reviews via code-reviewer subagent, and verification gates requiring evidence before any status claims. Essential for subagent-driven development, pull requests, and preventing false completion claims.
Planning agent that creates implementation plans and handoffs from conversation context
Persistent shared memory for AI agents backed by PostgreSQL (fts + pg_trgm, optional pgvector). Includes compaction logging and maintenance scripts.
OpenAI Agents SDK (Python) development. Use when building AI agents, multi-agent workflows, tool integrations, or streaming applications with the openai-agents package.
Coding patterns extracted from OpenAI Codex Rust codebase - a production CLI/agent system with strict error handling, async patterns, and workspace organization
Security audit enforcement for AI agents. Automated security scans and health verification.
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b
This skill should be used when the user mentions "openclaw", "OpenClaw CLI", asks to "send a message via openclaw", "manage openclaw agents", "configure openclaw gateway", "check openclaw status", "run openclaw agent", or asks about OpenClaw setup, channels, devices, or messaging automation.
Planning Agent: Converts project intent into a detailed execution plan. Responsible for defining detailed scope, WBS, dependencies, schedule, budget, and resource planning. Use after Intake/Charter is approved.