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Found 13 Skills
SOUL 自演进技能 — 在不可变段保护下更新可演进人格/协作策略并支持回滚。
Evolutionary self-improvement for Hermes Agent using DSPy + GEPA to optimize skills, prompts, and code
PUA Pro extensions: self-evolution tracking, compaction state protection, KPI reporting, and /pua commands. Triggers on: '/pua kpi', '/pua rank', '/pua weekly report', '/pua debriefing', '/pua flavor', 'self-evolution', 'evolution', or when users request PUA platform features such as rank/weekly report/debriefing.
A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution.
CRITICAL: Use for makepad-skills self-evolution and contribution. Triggers on: evolve, evolution, contribute, contribution, self-improve, self-improvement, add pattern, new pattern, capture learning, document solution, hooks, hook system, auto-trigger, skill routing, template, pattern template, shader template, troubleshooting template, 演进, 贡献, 自我改进, 添加模式, 记录学习, 文档化解决方案
Automated trading system management using Python and MetaTrader 5 API. V6.6 Predator Version with Infinite RR, Self-Evolution, and Triple-Resonance.
AI co-worker agent with its own computer, persistent memory, self-evolution, MCP server, and Slack/email identity built on Claude Agent SDK
Ecosystem self-evolution orchestrator. Detects project lifecycle phases, evaluates agent relevance, synthesizes cross-agent knowledge, and proposes evolution actions (health checks, fitness scoring, evolution proposals).
Create, validate, and convert skills for the agent ecosystem. Enforces standardized structure for consistency. Enables self-evolution by creating new skills on demand, converting MCP servers and codebases to skills.
Create and improve OpenAkita skills. It is used when you need to: (1) create new skills for repetitive tasks, (2) improve existing skills, (3) encapsulate temporary scripts into reusable skills. Skills are the core mechanism of OpenAkita's self-evolution.
Baidu FaMou algorithm skills for efficient algorithm self-evolution. Provides experiment management and visualization capabilities to help optimize complex algorithms. Use when user needs algorithm optimization or experiment management.
A curated collection of research papers and resources on agentic reasoning for Large Language Models, organized by planning, tool use, search, self-evolution, and multi-agent systems.