Individual skill

harness-evolve

Run `@metaharness/darwin evolve {repo}`: mutate a harness's seven policy surfaces, sandbox-score each variant and promote only measured wins. Use when evolving a harness against its tests or a bench suite. Degrades gracefully without darwin (ADR-150/153).

plugins/ruflo-metaharness/skills/harness-evolve/SKILL.md

Read pinned source

Source commit 722232566ad1fc4e73ba4fefc46d77d380ce61ba

What was checked

Matches the observed repository HEAD: Yes
Scanner rules are current: No
Repository scan complete: No
Skill scan complete: Yes
Observed behavior: Not checked yet
Last checked: Nov 6, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings): 81,269
Repository last updated: Nov 7, 2026
License: MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

swarm Repository topic
agentic-ai Repository topic
agentic-framework Repository topic
agentic-workflow Repository topic
autonomous-agents Repository topic
codex Repository topic
mcp-server Repository topic
multi-agent Repository topic
ai-assistant Repository topic
multi-agent-systems Repository topic
engineering Derived category

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files

SKILL.mdcore · 6,191 bytes

Read excerpt


Surfaces the upstream `metaharness-darwin evolve` CLI as a ruflo skill. The
**write** layer that pairs with ADR-150's read layer (score / genome /
mcp-scan / threat-model / oia-audit). Use when you have a harness whose
readiness scores are flat and you want to discover *which* surface mutation
moves them — without retraining the foundation model.

## When to use

- A `harness-score` result is below target and you don't know which policy
  surface is responsible.
- You're seeding a harness for a new vertical and want to find a good
  starting configuration empirically rather than hand-tuning.
- You're comparing your hand-tuned harness against an evolved baseline
  (treat darwin's champion as the strawman).