A comprehensive collection of meta-skills for Claude Code that enable self-management and reflection capabilities

Self-evolving AI daemon in Go with fully generative UI. LLM generates unique HTML/ANSI interfaces from scratch for every response — not templates, not component catalogs. 10-stage pipeline, 4-level reflection, fractal agents, auto-generated code skills, 6 input channels.

Give your AI agent an inner life. Emotions, dreams, reflection, memory, evolution. 6 modular skills for OpenClaw agents.

A modular Rust-based self-learning episodic memory system for AI agents, featuring hybrid storage with Turso (SQL) and redb (KV), async execution tracking, reward scoring, reflection, and pattern-based skill evolution. Designed for real-world applicability, maintainability, and scalable agent workflows.

Skills that make Claude Code improve itself. Self-evolving agent configuration via automated scouting, multi-model debate, and reflection.

🧠 A metacognitive reflection skill for AI agents, based on Kahneman's Thinking, Fast and Slow

Dremio developer CLI, and AI agent skills — query, catalog, schema, reflections, jobs, and access for Dremio Cloud

A neuroscience-backed learning partner skill for AI coding agents. Retrieval, spacing, reflection, interleaving, and more — while you build software.

A modular, domain-agnostic agent architecture based on a 12-layer cognitive model. Includes unified schemas, planning, world modeling, judgment, skill systems, episodic memory, reflection, and curriculum-driven goal selection. Local-first, backend-pluggable, fully composable.

Autonomous Agent that learns skills through implementation and reflection.

Advanced Reflection Skill for AI Agents - Multi-dimensional problem identification and improvement suggestions

🦉 OpenCode skill — error reflection & 5-Why root-cause learning agent

Agentic AI companion for kids: adaptive chat, voice, face/hand detection, skill tracking, and self-reflection.

A public log documenting my one year journey into AI Engineering — weekly notes, mini-projects, and reflections as I build skills in Python, LLMs, RAG, and AI Agents.

OpenClaw agent memory management skill — three-layer density structure, six-category write spec, session reflection, and flush protocol

Niuma is an AI agent system with cognitive abilities, collaboration capabilities, and autonomous execution skills, capable of handling complex multi-step tasks. Through multi-agent collaboration and reflection mechanisms, it continuously optimizes execution quality.

AI agent systems skill for Claude Code — ReAct, Plan-and-Execute, reflection loops, Tree of Thoughts, LATS, MCP integration, LangChain/LangGraph/CrewAI/AutoGen/Claude Agent SDK, multi-agent orchestration, evaluation. By TheGEOLab.net

🌟Hard Skills: System design, LLM Agent architecture, lifecycle management, agile prioritization 🔹 Practical Insights: Strategy reviews, OKRs, decision frameworks 🔹 Cognitive Growth: Sense training, user psychology, leadership reflection 🔸 AI Empowerment: AI productization, prompt engineering, Agent design

ADVERSARIAL AUTOPSY REQUIRED. The mission 'Autonomous Adaptive Trading Engine' FAILED.MASTER REFLECTION: QUALITY_SCORE: 1XP_AWARDED: 50NEW_TOPIC: [No new topic opened]SKILLS: [system_design, deployment, multi-agent_coordination]METRICS:Coordination: 2 - The agent attempted the task but failed to coORIGINAL ERROR LOGS:Ollama model did not return out

ADVERSARIAL AUTOPSY REQUIRED. The mission 'CURIOSITY: Project Mnemosyne: The Memory Sovereign.' FAILED.MASTER REFLECTION: QUALITY_SCORE: 1XP_AWARDED: 50NEW_TOPIC: SKILLS: [multi-agent_coordination, system_design, deployment]METRICS:Coordination: 1Technical Complexity: 8Efficiency: 1Clarity: 1SUGGEST_UI: FalseORIGINAL ERROR LOGS:DeepSeek/AI model di

ADVERSARIAL AUTOPSY REQUIRED. The mission 'Autonomous Trading Intelligence Network' FAILED.MASTER REFLECTION: QUALITY_SCORE: 1XP_AWARDED: 50NEW_TOPIC: [None]SKILLS: [multi-agent_coordination, system_design, deployment]METRICS:Coordination: 1Technical Complexity: 1Efficiency: 2Clarity: 1SUGGEST_UI: ORIGINAL ERROR LOGS:Ollama model did not return out

ADVERSARIAL AUTOPSY REQUIRED. The mission 'CURIOSITY: **Project Gethsemane**' FAILED.MASTER REFLECTION: QUALITY_SCORE: 1XP_AWARDED: 50NEW_TOPIC: [NONE]SKILLS: [system_design, clarity, multi-agent_coordination]METRICS:Coordination: 1Technical Complexity: 10Efficiency: 1Clarity: 1SUGGEST_UI: TrORIGINAL ERROR LOGS:DeepSeek/AI model did not return outp

ADVERSARIAL AUTOPSY REQUIRED. The mission 'Autonomous Research and Implementation Trading Engine' FAILED.MASTER REFLECTION: QUALITY_SCORE: 3XP_AWARDED: 100NEW_TOPIC:SKILLS: [system_design, multi-agent_coordination, automation]METRICS:Coordination: 2 - The agent did not successfully orchestrate the required componentsORIGINAL ERROR LOGS:Ollama model

ADVERSARIAL AUTOPSY REQUIRED. The mission 'Autonomous Evolutionary Trading System (AE-Trader)' FAILED.MASTER REFLECTION: QUALITY_SCORE: 2XP_AWARDED: 50NEW_TOPIC: [None]SKILLS: [coordination, system_design, deployment]METRICS:Coordination: 3 - Task was attempted but not completed, indicating a failure in agent or mORIGINAL ERROR LOGS:Ollama model di

ADVERSARIAL AUTOPSY REQUIRED. The mission 'Autonomous Modular Growth Engine (AMGE)' FAILED.MASTER REFLECTION: QUALITY_SCORE: 1XP_AWARDED: 50NEW_TOPIC: - SKILLS: [system_design, multi-agent_coordination, deployment]METRICS:Coordination: 1 - No integration or usable output was produced for the ecosystem.ORIGINAL ERROR LOGS:Ollama model did not return

ADVERSARIAL AUTOPSY REQUIRED. The mission 'CURIOSITY: Project Chimney Swift' FAILED.MASTER REFLECTION: QUALITY_SCORE: 1XP_AWARDED: 50NEW_TOPIC: [N/A]SKILLS: [system_design, automation, monetization]METRICS:Coordination: 1 - The agent failed to produce any usable output or demonstrate integration ORIGINAL ERROR LOGS:DeepSeek/AI model did not return

ADVERSARIAL AUTOPSY REQUIRED. The mission 'Autonomous Adaptive Evolutionary Network (AAEN)' FAILED.MASTER REFLECTION: QUALITY_SCORE: 2XP_AWARDED: 50NEW_TOPIC:SKILLS: [system_design, multi-agent_coordination, automation]METRICS:Coordination: 1Technical Complexity: 1Efficiency: 3Clarity: 2SUGGEST_UI: FalseSORIGINAL ERROR LOGS:Ollama model did not ret

ADVERSARIAL AUTOPSY REQUIRED. The mission 'CURIOSITY: Project Cerebellum' FAILED.MASTER REFLECTION: QUALITY_SCORE: 1XP_AWARDED: 50NEW_TOPIC:SKILLS: [system_design, analysis, multi-agent_coordination]METRICS:Coordination: 2 - Failed to return a result for integration or review.Technical CompleORIGINAL ERROR LOGS:DeepSeek/AI model did not return outp