molclaw-mol-topology-metrics
molclaw-mol-topology-metrics is a Chemistry & materials skill for AI agents, published by InternScience in the Agents-A1 repository on GitHub. Skillspace rates molclaw-mol-topology-metrics C (74/100) and it passed the safety scan; the rating is based on static analysis only.
Compute a comprehensive set of topological descriptors for a list of SMILES strings, returning the Topological Polar Surface Area (TPSA), a series of valence and non-valence molecular connectivity indices (Chi0–Chi4), the Hall–Kier alpha value, and Kappa shape indices (Kappa1–Kappa3) for each input molecule.
- Grade
- C
- Quality
- 74 / 100
- Safety
- Passed
- GitHub stars
- 469
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
- 99 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
- Scope
- Portable: works in any project. Generic cheminformatics descriptor computation from SMILES
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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