github.comrepo๐ง AIagentdescent is a Python framework that treats self-improving agents as an optimization problem: N workers propose diffs (edits) to a shared skill/prompt/harness artifact in parallel, and a barrier-free aggregator merges them via conflict resolution, fusion and statistical acceptance rather than gradient averaging, committing winners to a version-controlled ledger. It ships a single `evolve()` entry point with pluggable strategy, scorer, and proposal functions, an MCP server and CLI for agent-triggered runs, and faithful reimplementations of 20 published self-evolution algorithms (ACE, GEPA, EvoSkill, SkillOpt, ADAS, DGM, OpenEvolve, ERA, PromptBreeder, AFlow, Self-Refine, Reflexion, SICA, Gรถdel Agent, Voyager, SkillWeaver, Absolute Zero, R-Zero, Agent0, Genesis) that plug into the same engine for apples-to-apples comparison. The accompanying paper (Chen, 2026) gives a closed-form condition for when concurrent edits can merge and reports confidence intervals rather than false-precision p-values.
PythonHugging FaceModel Context Protocol+5
ACEGEPAEvoSkill+18
agents, evalsยท Added 30 Sep 2026, published 24 Jul 2026