level2-research
level2-research is a Physics, mathematics & simulation skill for AI agents, published by EdwardOptimization in the Bilevel-Autoresearch repository on GitHub. Skillspace rates level2-research D (66/100) and it passed the safety scan; the rating is based on static analysis only.
Meta-optimize any optimization loop. Reads your search/optimization code, diagnoses why it's stuck, and generates new mechanisms as injectable Python code — drawn from adjacent fields (combinatorial optimization, bandits, evolutionary algorithms, DOE, etc.). Works with any loop that does propose → evaluate → keep/discard. TRIGGER: "improve the loop", "meta-optimize", "why is my search stuck", "generate a new mechanism", "level 2", "bilevel", "break out of plateau", "my optimization keeps repeating", "add exploration to my loop", "inject a new strategy", "improve search diversity"
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 172
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
- 84 / 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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