Let Skills Evolve Collectively with Agentic Evolver
WikiSkill (arXiv:2608.27454) for Hermes Agent — self-evolving agent skills via a persistent knowledge wiki. Faithful Algorithm 1 implementation with real agent runs, isolated skill gating, and a documented live run log.
Bounded, evidence-driven SKILL.md evolution under frozen evaluation and safety contracts.
Evidence-driven skill evolution for Hermes Agent — reports, dry-run proposals, candidate search, and guarded apply
Evolving what multimodal agents see and how they read it. Framework, ten reusable task skills, and paper resources.
Flow-driven recursive skill evolution for agentic LLM orchestration.
A curated collection of papers & repos on Auto-Skill (self-evolving agents) and Auto-Rubric (rubric learning from preferences) for LLM alignment & customization.
Improve Claude Code and OpenAI Codex skills from real feedback, with evidence, regression checks, and human review.
SkillTV-Bench: a benchmark for evaluating, evolving, and analyzing judge skills on agent trajectories.
Multi-agent framework for Claude Code: tier-aware acceptance (S/M/L), acceptor/optimizer split, filesystem-isolated adversary review, cross-family second-opinion via Codex MCP, SkillOpt-style skill evolution, event ledger observability, human as supreme judge
Bionic memory for AI agents: GraphRAG, predictive memory, dream consolidation, governed skill evolution, MCP, REST API, and dashboard.
技能自进化系统 v2.0.0 — 8阶段Loop + 跨模型双裁判 + 30题测试集
WikiSkill: Compiling Agent Experience into Persistent Knowledge for Skill Evolution — for OpenCode, Claude Code, and Codex CLI
opencode plugin — Hermes-style self-improvement loop (port of UniM0cha/claude-self-improving-skills + okdk7788/skill-evolution). Distills learned skills after complex work + GEPA-style measured evolution.
数字员工操作系统 — AI agent 像真正员工一样工作、学习、成长的协作平台。3D 虚拟办公室 + 技能进化 + 职业发展 + 记忆系统
A control-theoretic learning plane for Hermes-style AI agents
Zero-dependency AI agent orchestration engine. Parallel DAG execution, skill genetics, ontology routing, human approval gates. 8.7K LOC, <1MB. The embeddable agent engine that learns.
Evolve AI agent skills through chat interactions that persist across devices and users with a collective learning framework.
MetaClaw fork: self-hosted GPU training (GRPO + LoRA + vLLM), per-agent skill isolation, multi-agent mode routing, training engine bug fixes. Train your AI agent on your own A100s. No cloud dependency.
天演·多引擎合一 Agent Skill 进化系统：判据校准→wiki知识编译→证据驱动编辑→防膨胀→四层门控→测试集生长→版本化发布
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