treatment-response-predictor-planner
treatment-response-predictor-planner is a Statistical modelling skill for AI agents, published by aipoch in the medical-research-skills repository on GitHub. Skillspace rates treatment-response-predictor-planner C (79/100) and it passed the safety scan; the rating is based on static analysis only.
Designs studies for predicting treatment response or resistance in biomedical and clinical research. Always use this skill when the user needs a treatment-response or resistance prediction study blueprint rather than a prognostic biomarker protocol, diagnostic test design, causal treatment-effect estimation, or a completed manuscript. Focus on responder definition, treatment context, baseline comparability, feature integration strategy, model development logic, validation architecture, and interpretation boundaries. Do not invent response rates, cohort size, assay readiness, regimen uniformity, literature support, or validation access.
- Grade
- C
- Quality
- 79 / 100
- Safety
- Passed
- GitHub stars
- 1,449
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
- 97 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 2 collections
- Scope
- Portable: works in any project. General clinical study-design methodology
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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