q2mm-benchmark
q2mm-benchmark is a Chemistry & materials skill for AI agents, published by ericchansen in the q2mm repository on GitHub. Skillspace rates q2mm-benchmark C (74/100) and it passed the safety scan; the rating is based on static analysis only.
MANDATORY before launching any q2mm batch optimization run >30 minutes (benchmark.py, multi-system convergence runs, from-QFUERZA runs, etc.). Forces success-spec write, optimizer config sanity check, FIRST-system audit gate before launching the rest, and post-batch validation. Use when user says "run benchmarks", "regenerate convergence results", "run all systems", "QFUERZA recovery", or any variant of launching a multi-system q2mm optimization batch.
- Grade
- C
- Quality
- 74 / 100
- Safety
- Passed
- GitHub stars
- 26
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
- 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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