Prompt Optimizer
SkillAI & modelsA/B test CLAUDE.md instruction changes against eval benchmarks. Capture baselines, test variants, compare results.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Prompt Optimizer skill
What this skill tells your AI
The instructions your AI receives, as published by haabe/mycelium in plugins/mycelium/skills/prompt-optimizer/SKILL.md and read by ahel’s review.
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
Signals
- GitHub stars
- 45
- Forks
- 3
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
prompt-optimizer-haabe- Source
- github.com/haabe/mycelium