quality-assessment
quality-assessment is a Bioinformatics & life sciences skill for AI agents, published by ammawla in the encode-toolkit repository on GitHub. Skillspace rates quality-assessment D (69/100) and it passed the safety scan; the rating is based on static analysis only.
Evaluate ENCODE experiment quality using standard metrics and audit flags. Use when the user asks about data quality, wants to filter for high-quality experiments, needs to interpret quality metrics (FRiP, NSC, RSC, NRF, IDR, TSS enrichment, fragment size), wants to understand ENCODE audit warnings, needs to compare quality across experiments, or is deciding whether data is usable for their analysis. Also use when the user mentions QC, quality control, or data filtering.
- Grade
- D
- Quality
- 69 / 100
- Safety
- Passed
- GitHub stars
- 37
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
- 90 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- AGPL-3.0
- Adoption
- Adopted by 0 other repositories, in 1 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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