molclaw-drug-likeness

molclaw-drug-likeness is a Chemistry & materials skill for AI agents, published by InternScience in the Agents-A1 repository on GitHub. Skillspace rates molclaw-drug-likeness C (70/100) and it passed the safety scan; the rating is based on static analysis only.

Compute the drug-likeness metrics (QED score and Number of violations of Lipinski's Rule of Five) of the input candidate molecules (SMILES format).

Grade
C
Quality
70 / 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.

View source on GitHubInternScience/Agents-A1

Our review

Architecture
92 / 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

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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