# harness-evolver

This plugin evolves an AI agent’s code and evaluates candidate changes with LangSmith. Use it to test changes to prompts, routing, or tools against project data.

- plugin · `type=plugin` · Claude Code · ★ 57
- Author: raphaelchristi
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/raphaelchristi/harness-evolver
- Updated: 2026-04-18
- HTML: https://affpapa.org/en/nevibecode/plugins/harness-evolver

## What it does

harness-evolver launches parallel proposer agents in separate Git worktrees. They edit the agent’s code, while LangSmith runs experiments and an LLM judge scores candidates. The plugin merges winning changes automatically; regression checks can reject a candidate.

The loop also includes critic, architect, evaluator, and test-generation agents. Run `/harness:evolve` to start optimization, or `/harness:setup` to inspect the project and configure LangSmith. You need a LangSmith account with `LANGSMITH_API_KEY`, Python 3.10+, and Git. Candidate evaluation depends on access to LangSmith.

## Install

### Claude Code (native platform)

**Plugin marketplace**
In the agent chat (not a shell):
```text
/plugin marketplace add anthropics/claude-plugins-community
```
In the agent chat (not a shell):
```text
/plugin install harness-evolver@claude-community
```

## When to use it
- test prompt variants against a LangSmith dataset
- change an agent’s routing and tools
- reject candidates that regress on evaluation data
- compare code variants and merge the winning candidate

## Example prompts
- Set up the project and LangSmith with `/harness:setup`.
- Run an evolution cycle on my AI agent with `/harness:evolve`.
- Check the dataset’s condition with `/harness:health`.

## Source text · SKILL.md · MIT

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````text
<p align="center">
  <img src="assets/banner.jpg" alt="Harness Evolver" width="100%">
</p>

# Harness Evolver

<p align="center">
  <a href="https://www.npmjs.com/package/harness-evolver"><img src="https://img.shields.io/npm/v/harness-evolver?style=for-the-badge&color=blueviolet" alt="npm"></a>
  <a href="https://github.com/raphaelchristi/harness-evolver/blob/main/LICENSE"><img src="https://img.shields.io/badge/License-MIT-green?style=for-the-badge" alt="License: MIT"></a>
  <a href="https://arxiv.org/abs/2603.28052"><img src="https://img.shields.io/badge/Paper-Meta--Harness-FFD700?style=for-the-badge" alt="Paper"></a>
  <a href="https://github.com/raphaelchristi/harness-evolver"><img src="https://img.shields.io/badge/Built%20by-Raphael%20Valdetaro-ff69b4?style=for-the-badge" alt="Built by Raphael Valdetaro"></a>
</p>

Point at any LLM agent codebase. Harness Evolver will autonomously improve it — prompts, routing, tools, architecture — using multi-agent evolution with LangSmith as the evaluation backend.

---

## Install

### Claude Code Plugin (recommended)

```
/plugin marketplace add raphaelchristi/harness-evolver-marketplace
/plugin install harness-evolver
```

### npx (first-time setup or non-Claude Code runtimes)

```bash
npx harness-evolver@latest
```

Works with Claude Code, Cursor, Codex, and Windsurf.

---

## Quick Start

```bash
cd my-llm-project
export LANGSMITH_API_KEY="lsv2_pt_..."
claude

/harness:setup      # explores project, configures LangSmith
/harness:health     # check dataset quality (auto-corrects issues)
/harness:evolve     # runs the optimization loop
/harness:status     # check progress (rich ASCII chart)
/harness:deploy     # tag, push, finalize
```

---

## What It Looks Like

Tested on a RAG agent (Agno framework, Gemini 3.1 Flash Lite, light mode):

```mermaid
xychart-beta
    title "agno-deepknowledge: 0.575 → 1.000 (+74%)"
    x-axis ["base", "v001", "v002", "v003", "v004", "v005", "v006", "v007"]
    y-axis "Correctness" 0 --> 1
    line [0.575, 0.575, 0.950, 0.950, 0.950, 0.950, 0.950, 1.0]
    bar [0.575, 0.333, 0.950, 0.720, 0.875, 0.680, 0.880, 1.0]
```

| Iter | Score | Merged? | What the proposer did |
|---|---|---|---|
| baseline | 0.575 | — | Original agent — hallucinations, broken tool calls, no retry logic |
| v001 | 0.333 | Yes | Anti-hallucination prompt (100% correct when API responded, but 60% hit rate limits) |
| v002 | 0.950 | Yes | **Breakthrough**: inlined 17-line KB into prompt, eliminated vector search entirely. 5.7x faster, zero rate limits |
| v003 | 0.720 | **No** | Attempted hybrid retrieval — regressed, rejected by constraint gate |
| v004 | 0.875 | **No** | Response completeness fix — improved one case but regressed others |
| v005 | 0.680 | **No** | Reduced tool calls — broke edge cases, rejected |
| v006 | 0.880 | Yes | Evolution memory insight: combined v001's anti-hallucination with one-shot example from archive |
| v007 | 1.000 | Yes | One-shot example injection + rubric-aligned responses — perfect on held-out |

The line shows best score (only goes up — regressions aren't merged). The bars show each candidate's raw score. 4 merged, 3 rejected by gate checks. Not every iteration improves — that's the point.

---

## How It Works

| | |
|---|---|
| **LangSmith-Native** | No custom scripts. Uses LangSmith Datasets, Experiments, and LLM-as-judge. Everything visible in the LangSmith UI. |
| **Real Code Evolution** | Proposers modify actual code in isolated git worktrees. Winners merge automatically. |
| **Self-Organizing Proposers** | Two-wave spawning, dynamic lenses from failure data, archive branching from losing candidates. Self-abstention when redundant. |
| **Rubric-Based Evaluation** | LLM-as-judge with justification-before-score, rubrics, few-shot calibration, pairwise comparison. |
| **Smart Gating** | Constraint gates, efficiency gate (cost/latency pre-merge), regression guards, Pareto selection, holdout enforcement, rate-limit early abort, stagnation detection. |

[Full feature list](docs/FEATURES.md)

---

## Evolution Loop
````
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First 4095 of 7601 bytes. © raphaelchristi · MIT · https://github.com/raphaelchristi/harness-evolver

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From the same set: [raphaelchristi/harness-evolver](https://affpapa.org/en/nevibecode/by/raphaelchristi/harness-evolver.md) — 10 cards

---
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