implement-constraint
implement-constraint is a Bioinformatics & life sciences skill for AI agents, published by evo-design in the proto-language repository on GitHub. Skillspace rates implement-constraint D (57/100) and it passed the safety scan; the rating is based on static analysis only.
Implements, modifies, or debugs constraints in the proto-language DSL. Covers the full lifecycle: BaseConfig class with ConfigField, scoring function returning list[ConstraintOutput], @constraint decorator registration, 3-level export chain, and pytest test coverage. Use when working with constraints, scoring functions, GC content, structure prediction scores (pLDDT, pTM, pAE), protein quality, sequence motifs, RNA structure, or splicing predictions.
- Grade
- D
- Quality
- 57 / 100
- Safety
- Passed
- GitHub stars
- 153
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
- 80 / 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
- Category is a classifier prediction; no model has read this skill 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
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.