Infrastructure for continually self‑improving agents
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.
A research framework for principled agent self-improvement under frozen evaluators and declared mutation boundaries, recording verifiable lineage to make it reproducible and auditable.
Self-Improving Agents -- A Progression Four levels of self-improving code agents, from the simplest loop to a full adversarial arena with self-modifying agents. Each level adds one key idea.
FaustBot 是一个 AI 驱动的 Vtuber / 桌面伙伴。
Agent-assisted and full-agent reproducibility package for MLSys 2026 FlashInfer AI Kernel Generation Contest submissions: kernels, agent workflows, skills, configs, writeup, benchmark artifacts, and full optimization records.
Beastmode: MofA (Mixture of Agents) orchestration framework for Hermes/OpenClaw/Codex with MemroOS-style context continuity.
Agent skill for running Codex or Claude Code as an orchestrator over Symphony workers and Linear issues. Plans waves, dispatches workers, reviews and merges, and optionally pursues a goal across many waves under hard budget caps.
A governed learning layer for AI agents — turns execution traces into reviewed memories, reusable skills, and evidence-backed training data.
A lightweight, declarative agent harness — define multi-agent workflows as YAML, run them from Python or the CLI, and they get measurably better every run.
Shogun AFM is Agent Fleet Management for self-improving AI agents — combining agent orchestration, persistent memory, fleet monitoring, governance, security posture, and Gensui command control.
Build self-evolving AI agent harnesses with portable harness units, artifact-aware testing, trace-backed diagnosis, and evidence-gated promotion.
Collections of recursive self-improvement (RSI): papers where the loop that improves a system also changes the thing doing the improving.
Evidence-gated Recursive Self-Improvement (RSI) runtime for self-improving LLM agents, self-evolving agents, agentic AI, AI safety, evaluation, lineage, and rollback.
ACE — Agentic Context Engineering: evolving, self-improving context playbooks for LLM agents. Faithful ICLR 2026 implementation with OpenAI Agents SDK support.
Self-owned TerminalBench 2.0 coding-agent harness with a Rust Worker, Harbor/verifier-grounded evaluation, and guarded Heuristic Learning.
An evidence-driven map of Recursive Self-Improvement: systems, scorecards, benchmarks, research papers and live project radar.
An open standard for governed agent self-improvement: a self-modification that is proven, gated, recorded, reversible, and portable.
Proof-gated evolution for AI agents. Agents mutate. Evidence decides.
Self-improving repo health remediation skill with audit/fix/diff modes, evidence coverage, counter-review, and stable HP-* findings.
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