optimization
optimization is a Backend performance & caching skill for AI agents, published by 1jehuang in the jcode repository on GitHub. Skillspace rates optimization D (64/100) and it passed the safety scan; the rating is based on static analysis only.
Use when improving performance, latency, throughput, memory usage, or general efficiency. Start by defining target metrics, measuring comprehensively, attributing bottlenecks, validating with static analysis, and prioritizing macro-optimizations before micro-optimizations.
- Grade
- D
- Quality
- 64 / 100
- Safety
- Passed
- GitHub stars
- 8,341
Unproven: rated by static analysis only, not yet compared head-to-head.
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
- Low-risk patterns
- License
- MIT
- Adoption
- Adopted by 6 other repositories, in 3 collections
- Scope
- Portable: works in any project. Generic performance-optimization methodology applicable to any system
What the scanner flagged
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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