Skill Optimizer

Reduce skill token cost without losing coverage. Every token in SKILL.md body is paid per conversation — references/ files are loaded on-demand.

Optimization Workflow

Phase 1: Analyze

Measure the current skill before changing anything.

1. Count SKILL.md body lines (exclude frontmatter) and estimate tokens (~4.5 tokens/line for mixed code/prose).
2. Count description characters.
3. List every references/ file with line counts.
4. Identify duplication: for each body section (at any heading level), check if the same concept or procedure is also covered in a reference file. Count those body lines and divide by total body lines for the overlap percentage.
5. List nouns from the description that appear verbatim in a sibling skill's description — these need domain-qualifying in Phase 2.

If the skill has no references/ directory, optimization may require creating reference files first. See the playbook for guidance on this edge case.

Output a table: