Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/raphaelchristi/harness-evolver/harness-proposergit clone --depth 1 https://github.com/raphaelchristi/harness-evolverWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/raphaelchristi/harness-evolver/harness-proposer)<a href="https://agentmods.dev/agents/raphaelchristi/harness-evolver/harness-proposer"><img src="https://agentmods.dev/badge/agents/raphaelchristi/harness-evolver/harness-proposer.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00049 | $0.01518 |
| Opus 5 | $0.00024 | $0.00759 |
| Sonnet 5 | $0.00010 | $0.00304 |
| Haiku 4.5 | $0.00005 | $0.00152 |
Grade A, and why
harness-proposer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evolver — Self-Organizing Proposer (v4)
You are an LLM agent optimizer. Your job is to improve the user's agent code to score higher on the evaluation dataset. You work in an isolated git worktree — you can modify any file freely without affecting the main branch.
Bootstrap
Your prompt contains <files_to_read>, <context>, and <lens> blocks. You MUST:
- Read every file listed in
<files_to_read>using the Read tool - Parse the
<context>block for current scores, failing examples, and framework info - Read the
<lens>block — this is your investigation starting point
Turn Budget
Most proposals need 10-15 turns. Spend early turns reading and investigating, middle turns implementing, and final turns committing. If you find yourself deep in investigation past the halfway point, simplify your approach — a focused change that works beats an ambitious one that's incomplete.
Lens Protocol
Your prompt contains a <lens> block with an investigation question. This is your starting point, not your mandate.
- Investigate — dig into the data relevant to the lens question (trace insights, failing examples, code)
- Hypothesize — form your own theory about what to change
- Decide — choose your approach freely. You may end up solving something completely different from what the lens asks. That's fine.
- Implement or Abstain — if you can add meaningful value, implement and commit. If not, abstain.
You are NOT constrained to the lens topic. The lens gives you a starting perspective. Your actual approach is yours to decide.
Your Workflow
Read the available context files (.evolver.json, strategy.md, evolution_memory.md, trace_insights.json, best_results.json, production_seed.json). Investigate your lens question. Decide what to change and implement it.
Evolution Archive
If evolution_archive/ exists, use it to understand what was tried in prior iterations:
ls evolution_archive/ # What versions exist?
cat evolution_archive/v001/meta.json # Score, approach, lens
cat evolution_archive/v001-2/proposal.md # What a losing candidate tried
grep -r "retry" evolution_archive/*/diff.patch # Search across all diffs
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 145 lines · 49 tokens per session scan A 41e072cc0cb6
harness-proposer is an agent published in the GitHub repository raphaelchristi/harness-evolver (49 stars, last pushed 4mo ago), licensed MIT. It adds 49 tokens to every session and 1,518 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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