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 skills/raphaelchristi/harness-evolver/evolvenpx skills add raphaelchristi/harness-evolver --skill evolvegit clone --depth 1 https://github.com/raphaelchristi/harness-evolverWhat 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 | $0.00043 | $0.03865 |
| Opus 5 | $0.00022 | $0.01932 |
| Sonnet 5 | $0.00009 | $0.00773 |
| Haiku 4.5 | $0.00004 | $0.00386 |
Grade A, and why
harness:evolve scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 326 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/harness:evolve
Run the propose-evaluate-iterate loop. LangSmith is the evaluation backend, git worktrees provide isolation.
Setup
.evolver.json must exist. If not, tell user to run harness:setup.
TOOLS="${EVOLVER_TOOLS:-$([ -d ".evolver/tools" ] && echo ".evolver/tools" || echo "$HOME/.evolver/tools")}"
EVOLVER_PY="${EVOLVER_PY:-$([ -f "$HOME/.evolver/venv/bin/python" ] && echo "$HOME/.evolver/venv/bin/python" || echo "python3")}"
Never pass LANGSMITH_API_KEY inline. Tools resolve it automatically via _common.ensure_langsmith_api_key().
Arguments
--iterations N(default: ask or 5)--mode light|balanced|heavy— override mode from config--no-interactive— skip prompts, use defaults (for cron/background runs)
If interactive, ask iterations (3/5/10), target score (0.8/0.9/0.95/none), and execution mode (interactive/background).
Mode Parameters
MODES = {
"light": {"proposers": 2, "waves": 1, "concurrency": 5, "timeout": 60, "sample": 10, "analysis": "summary", "pairwise": False, "archive": "winner"},
"balanced": {"proposers": 3, "waves": 2, "concurrency": 3, "timeout": 120, "sample": None, "analysis": "summary", "pairwise": "if_close", "archive": "all"},
"heavy": {"proposers": 5, "waves": 2, "concurrency": 3, "timeout": 300, "sample": None, "analysis": "full", "pairwise": True, "archive": "all"},
}
Read mode from config, allow --mode override:
MODE=$(python3 -c "import json; print(json.load(open('.evolver.json')).get('mode', 'balanced'))")
If not --no-interactive, confirm or switch:
{
"question": "Mode: {MODE}. Continue?",
"header": "Mode",
"options": [
{"label": "Yes, continue with {MODE}"},
{"label": "Switch to light (~2 min/iter)"},
{"label": "Switch to balanced (~8 min/iter)"},
{"label": "Switch to heavy (~25 min/iter)"}
]
}
If changed, update config and re-read MODE.
Pre-Loop
Preflight
$EVOLVER_PY $TOOLS/preflight.py --config .evolver.json
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.
- 2d ago First seen · 326 lines · 43 tokens per session scan A 448d9144443a
harness:evolve is a skill published in the GitHub repository raphaelchristi/harness-evolver (49 stars, last pushed 4mo ago), licensed MIT. It adds 43 tokens to every session and 3,865 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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