Infrastructure for continually self‑improving agents
A curated research map of Recursive Self-Improvement (RSI): models, agents, harnesses, embodied systems, automated AI R&D, benchmarks, and safety.
A curated list for Self-Improvement in Foundation Model Based Agentic Systems.
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.
Continual agent skill evolution through persistent decision history. Whole-skill optimisation (SKILL.md + scripts + references) with every decision landing as a local Git issue / PR / wiki. Runs on any agentskills.io runtime — Claude Code, Codex, OpenClaw, Hermes.
FaustBot 是一个 AI 驱动的 Vtuber / 桌面伙伴。
A curated, evidence-aware collection of recursive self-improvement research, agents, harnesses, benchmarks, and safety work.
Where agents build agents. An open-source Rust framework for complex agentic systems: ontology-grounded, auditable, one binary.
The Dream Machine — a config-driven engine for nightly, cloud-scheduled, evidence-gated repository evolution. Composes @metaharness/flywheel, darwin, and redblue behind a promotion gate that never merges.
ThumbGate Pre-Action Checks self-improve from ranked lessons and repeated failures, hard-block detected secret leaks, and block matches in strict mode.
Methodology and deterministic evaluation tools for iterative improvement of skills, repositories and agent workflows, with independent review and regression checks.
Self-improving agents, governed. Areev is the substrate for adaptive agents — agents that get better from their own history, under human authority, in steps you can inspect, undo, and re-measure.
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.
DeepSeek Harness (DSH) plugin for self-improving AI agents: continual learning, persistent memory, cross-session knowledge, review-and-refine workflows, and automatic rollback.
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.
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