text-based-molecule-editing
text-based-molecule-editing is a Chemistry & materials skill for AI agents, published by PharMolix in the OpenBioMed repository on GitHub. Skillspace rates text-based-molecule-editing C (78/100) and it passed the safety scan; the rating is based on static analysis only.
Modify molecules based on natural language descriptions using MolT5/BioT5 models. Use this skill when: (1) User wants to modify a molecule to improve specific properties (solubility, potency, etc.), (2) User provides a molecule and asks to "make it more X" or "improve Y", (3) User wants to generate molecule variants guided by text descriptions. Triggers on phrases like "modify this molecule", "edit the molecule", "make it more soluble", "improve drug-likeness", "change the molecule to", "optimize this compound".
- Grade
- C
- Quality
- 78 / 100
- Safety
- Passed
- GitHub stars
- 1,090
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
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
- Scope
- Vendor-specific: built around one product. Uses public MolT5/BioT5 models via OpenBioMed toolkit
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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