Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/GuitarAlchemist/ganpx agentmods add skills/guitaralchemist/ga/auto-optimizeWrote 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/skills/guitaralchemist/ga/auto-optimize)<a href="https://agentmods.dev/skills/guitaralchemist/ga/auto-optimize"><img src="https://agentmods.dev/badge/skills/guitaralchemist/ga/auto-optimize/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/guitaralchemist/ga/auto-optimize"><img src="https://agentmods.dev/badge/skills/guitaralchemist/ga/auto-optimize.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00093 | $0.04453 |
| Opus 5.5 | $0.00037 | $0.01781 |
| Sonnet 5.5 | $0.00019 | $0.00891 |
| Haiku 4.5 | $0.00009 | $0.00445 |
Grade A, and why
Auto-Optimize 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 1mo 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 — 361 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/auto-optimize
The generalized version of the chatbot-improvement-loop runbook
(docs/runbooks/chatbot-improvement-loop.md). Where /chatbot-iterate
is hard-wired to the chatbot corpus, this skill is parameterized by
domain so the same Cherny pattern applies to any quality-metric loop
in the workspace (chatbot-qa, embeddings, voicing-analysis, optick-sae,
chatbot golden-trace signatures, etc.).
This is the Level 3 automation in the chatbot-development ladder:
assistant runs cycle-by-cycle without per-cycle human approval, with
hard caps + killswitch + Harness rollback validator gating every
commit. Level 4 (auto-merge on multi-LLM green) is still gated behind
Phase 2's Ollama-vs-cloud signal measurement (see docs/plans/ 2026-05-14-arch-cherny-adoption-and-tribunal-ci-plan-v2.md §Phase 2,
item 6).
Inputs
Pass via skill args as key=value pairs:
| Input | Required | Example |
|---|---|---|
domain |
yes | chatbot-qa, embeddings, voicing-analysis, optick-sae |
oracle_script_path |
yes | Scripts/run-prompt-corpus.ps1 |
baseline_path |
yes | state/quality/chatbot-qa/baseline.json |
max_iterations |
no (10) | hard cap on cycles per invocation |
plateau_window |
no (5) | how many consecutive sub-threshold improvements before exit |
plateau_threshold |
no (0.005) | minimum relative metric delta to count as progress |
The domain value drives every path computed by the skill — lock,
artifact dir, protected paths, etc. Picking a domain value that
doesn't already have a state/quality/<domain>/baseline.json is an
error; see Step 0.
Iron Laws
1. NEVER commit without the roundtrip validator passing.
2. NEVER edit a protected file (declared in baseline._protected_paths
or matching the global protected-paths-hook pattern).
3. NEVER exceed max_commits_per_session=50 or max_wall_clock_minutes=480.
4. ALWAYS release the .lock on exit (success, failure, or kill).
5. ALWAYS check state/.loop-halted and the per-domain .STOP marker
BEFORE every iteration, not just at start.
6. SELF-GOVERN from the ledger via `Scripts/loop-decide.ps1` (Step 3.9):
`stop-plateau` → exit; `halt-oscillating` / `halt-misfire` → halt AND
emit an algedonic signal (escalate, never silent). The loop decides when
to stop from the durable trajectory — not a fixed count, not its own
optimism. Stopping at the right time IS the job; it is not failure.
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.
- 1mo ago First seen · 361 lines · 93 tokens per session scan A 1381b9bf0795
Auto-Optimize is a skill published in the GitHub repository GuitarAlchemist/ga (2 stars, last pushed yesterday), licensed MIT. It adds 93 tokens to every session and 4,453 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-31.
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