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/haabe/mycelium/prompt-optimizernpx skills add haabe/mycelium --skill prompt-optimizergit clone --depth 1 https://github.com/haabe/myceliumWrote 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/haabe/mycelium/prompt-optimizer)<a href="https://agentmods.dev/skills/haabe/mycelium/prompt-optimizer"><img src="https://agentmods.dev/badge/skills/haabe/mycelium/prompt-optimizer.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 | $0.00027 | $0.00527 |
| Opus 5 | $0.00014 | $0.00264 |
| Sonnet 5 | $0.00005 | $0.00105 |
| Haiku 4.5 | $0.00003 | $0.00053 |
Grade A, and why
prompt-optimizer 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 5d 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.
What it actually says
Prompt Optimizer
Systematically improve Mycelium instructions through measurement. Adapted from n-trax.
Commands
baseline -- Capture current performance
- Run
/mycelium:eval-runner run-split optimization— record as optimization scores - Run
/mycelium:eval-runner run-split holdout— record as holdout scores - Record both to
.claude/optimization/baseline.json: timestamp, CLAUDE.md hash, optimization metrics, holdout metrics, overall and per-category metrics
test <variant> -- Test a variant
- Read variant from
.claude/optimization/variants/<variant>.md - Apply the CLAUDE.md changes described
- Run
/mycelium:eval-runner run-split optimization— this is the hill-climbing signal - Run
/mycelium:eval-runner run-split holdout— this validates generalization - Store results in
.claude/optimization/results/<variant>.json - Compare against baseline. Flag overfitting if optimization improves but holdout degrades.
- Do NOT auto-revert -- let user decide
report -- Compare all variants
Generate comparison table with split-aware columns:
| Variant | Opt Pass Rate | Holdout Pass Rate | Delta Opt | Delta Holdout | Overfit? | Decision |
Flag Overfit? = YES when optimization delta is positive but holdout delta is negative.
exemplar <eval-name> -- Capture winning trajectory
After a clean eval win (1 iteration, fast), save the approach to .claude/optimization/exemplars/.
Workflow
- Capture baseline
- Hypothesize an instruction improvement
- Document in variants/ directory
- Test the variant
- Compare via report
- Keep or revert based on data
- Capture exemplars from clean wins
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.
- 5d ago First seen · 48 lines · 27 tokens per session scan A b253c400e961
prompt-optimizer is a skill published in the GitHub repository haabe/mycelium (45 stars, last pushed today), licensed MIT. It adds 27 tokens to every session and 527 once invoked, about $0.0001 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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