autoharness

tigerless-labs/autoharness is an open-source project by tigerless-labs: Autoharness — a self-learning skill layer for Claude Code — distills skills from your real sessions, updates them as you work, and prunes the ones that stop getting used. No daemon, no benchmark.. Indexed here so it can be found — not resold.

It is free. Get it from the upstream repository: https://github.com/tigerless-labs/autoharness

From the project's own README (excerpt, reproduced for discovery under its MIT license):

AutoHarness Self-Learning Skills for Claude Code

autoharness is a self-learning skill layer for Claude Code. It learns skills from your real sessions, merges same-scenario ones instead of stacking near-duplicates, updates them in use, and prunes any that stop getting used — so the layer stays clean on its own, touching only the skills it wrote itself.

Same model, different harness — 42% → 78% on CORE-Bench (HAL). The harness does much of the work (swyx's Big Model vs Big Harness), yet it's still rebuilt by hand every model generation. autoharness bets one slice of it — the skill layer — can maintain itself.

--- --- Learns from real work Each episode is distilled into a skill from the session you were already having — no separate data-collection or replay loop. It fires on its own once a session has done enough work; /learn distills on demand when you want a lesson kept now. Groups, doesn't just pile up A new episode doesn't always add a skill — the reflector compares it against what's there and folds same-scenario skills into one, so the layer consolidates by category instead of accreting near-duplicates. A fold records which skill absorbed which, so a merge is never mistaken for a death. Keeps its own library in view Every session opens with a grouped index of the skills it wrote, so recall doesn't depend on the host happening to surface them. The host's native recall is left exactly as it was; the index is added on top. Validated in use, not on a benchmark A skill survives by being adhered to in later turns (loads over the requests it was available for), not a held-out score. No oracle on the active path, and no tokens spent on a dedicated eval. Only its own skills Touches only the skills it generated through this plugin — everything else,…