prompt-optimizer

name	prompt-optimizer
description	A/B test CLAUDE.md instruction changes against eval benchmarks. Capture baselines, test variants, compare results.
metadata	{"instruction_budget":"17","framework_dependency":"mycelium","framework_dependency_note":"This skill is designed to run within the Mycelium framework (https://github.com/haabe/mycelium). Standalone use will skip the canvas state, theory gates, and harness behavior the skill assumes. Install: /plugin install mycelium@haabe-mycelium."}

Prompt Optimizer

Systematically improve Mycelium instructions through measurement. Adapted from n-trax.

Commands

baseline -- Capture current performance

1. Run /mycelium:eval-runner run-split optimization — record as optimization scores
2. Run /mycelium:eval-runner run-split holdout — record as holdout scores
3. 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

1. Read variant from .claude/optimization/variants/<variant>.md
2. Apply the CLAUDE.md changes described
3. Run /mycelium:eval-runner run-split optimization — this is the hill-climbing signal
4. Run /mycelium:eval-runner run-split holdout — this validates generalization
5. Store results in .claude/optimization/results/<variant>.json
6. Compare against baseline. Flag overfitting if optimization improves but holdout degrades.
7. 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

1. Capture baseline
2. Hypothesize an instruction improvement
3. Document in variants/ directory
4. Test the variant
5. Compare via report
6. Keep or revert based on data
7. Capture exemplars from clean wins