ClawHub

Equity Scorer

v0.2.0

Compute HEIM diversity and equity metrics from VCF or ancestry data. Generates heterozygosity, FST, PCA plots, and a composite HEIM Equity Score with markdow...

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by@manuelcorpas
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
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Purpose & Capability
The name/description (HEIM diversity/equity scoring) match what the code and SKILL.md implement: VCF/CSV parsing, heterozygosity, pairwise FST, PCA, plotting, and a composite HEIM score. Requested binaries (python3) and Python libraries (numpy, pandas, scikit-learn, matplotlib, biopython) are appropriate for these tasks.
✓
Instruction Scope
SKILL.md describes only dataset parsing, metric computation, plotting, and writing a markdown report and reproducibility artifacts. The included code snippet operates on local input files and computes statistics; there are no instructions to read unrelated system files, access external endpoints, or collect secrets.
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Install Mechanism
Install spec uses 'uv' package entries for standard Python packages (biopython, pandas, scikit-learn, matplotlib, numpy). Installing common Python packages is expected, but 'uv' as the install kind is unusual (not the common pip/conda labels) — verify what 'uv' maps to in your agent environment and that packages will come from a trusted registry. No arbitrary URL downloads or archive extraction are declared.
✓
Credentials
The skill requires no environment variables, no credentials, and no config paths. That is proportionate to the described functionality (local analysis of genomic/metadata files).
✓
Persistence & Privilege
always is false and there is no request to modify other skills or system-wide settings. The skill does not request persistent elevated presence or permissions.
Assessment
This skill appears to implement what it claims: local reading of VCF/CSV inputs, computation of population genetics metrics, plotting, and writing a report. Before installing: 1) Confirm what the registry's 'uv' installer does in your environment (ensure packages come from trusted PyPI/conda sources). 2) Prefer installing/running in a sandbox or virtual environment to avoid contaminating system Python. 3) The registry metadata had 'Source: unknown' / no homepage, while SKILL.md references a GitHub URL — if provenance matters, inspect the upstream repository to ensure the code matches and no extra files/scripts are added. 4) Tests reference example data under an examples/ path which is not present in the manifest; if you plan to run tests end-to-end, obtain the demo input files from the author/repo. If these checks look good, the skill is coherent and does not request secrets or network access.

Like a lobster shell, security has layers — review code before you run it.

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License

MIT-0
Free to use, modify, and redistribute. No attribution required.
Termshttps://spdx.org/licenses/MIT-0.html

Runtime requirements

🦖 Clawdis
OSmacOS · Linux
Binspython3

Install

uvuv tool install biopython
uvuv tool install pandas
uvuv tool install scikit-learn
uvuv tool install matplotlib
uvuv tool install numpy

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