perf-optimization
perf-optimization is a Runtime diagnostics & profiling skill for AI agents, published by irahardianto in the awesome-agv repository on GitHub. Skillspace rates perf-optimization D (69/100) and it passed the safety scan; the rating is based on static analysis only.
Profile-driven performance optimization protocol. Use when profiling data (CPU, heap, trace) is available or when the user requests performance analysis. Covers methodology (Profile → Analyze → Opportunity Scan → Prioritize → Optimize → Benchmark), optimization pattern catalog, safety invariants, and when-to-stop heuristics. Language-specific tooling is in languages/*.md.
- Grade
- D
- Quality
- 69 / 100
- Safety
- Passed
- GitHub stars
- 150
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
- 78 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked 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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