performance-optimization
performance-optimization is a Runtime diagnostics & profiling skill for AI agents, published by UnpaidAttention in the fable5-methodology repository on GitHub. Skillspace rates performance-optimization D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Make code measurably faster or leaner without breaking it — define a target, measure a baseline, profile to find the ACTUAL bottleneck, apply optimizations in a fixed order of leverage, and re-verify correctness after each change. Trigger this when the user reports slowness, high latency, memory growth, or cost, sets a performance budget, or asks to "optimize" or "speed up" something. Do NOT trigger for functional bugs that happen to involve timing (use debugging-methodology) or for restructuring at equal performance (use safe-refactoring) — this skill exists to move a number.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 83
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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