predict-runtime-breakdown
predict-runtime-breakdown is a Bioinformatics & life sciences skill for AI agents, published by rdk in the p2rank repository on GitHub. Skillspace rates predict-runtime-breakdown D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Produce a detailed phase-by-phase runtime breakdown of a single `prank predict` run (JVM boot, class-loading, Groovy config compile, model load, PDB parse, surface, feature extraction, prediction, output) on the current JRE. Use when asked where p2rank prediction time goes, to profile startup/runtime overhead, to find what to optimize, or to compare launchers/JVMs at sub-phase granularity.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 444
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
- 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
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.