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onekgpd

Queries the 1000 Genomes Project dataset (3,202 whole-genome-sequenced individuals, GRCh38) at the level of individual participants. Use when a question is about individuals or variants in the 1000 Genomes Project cohort: which individuals carry variants matching specific criteria in a gene or region, which individuals are homozygous-reference at a position, which variants exist in the dataset or carried by specified individuals in a gene or region, the relatedness between two specified individuals. Variants are returned with 1000 Genomes allele frequencies (AF), gnomAD v4.1 exome and genome AF, AlphaMissense score, and HGVSp annotations.

75

Quality

94%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

92%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-engineered skill body: fully executable commands with a complete worked example, count-before-select validation checkpoints with explicit incomplete/truncated recovery guidance, and a clean one-level-deep split between the overview and two reference files. The main improvable point is redundancy — Quick Start and Typical Workflows duplicate the same command sequence, and the question-to-command mapping is stated twice.

Suggestions

Collapse 'Typical Workflows' into the Quick Start (or reduce it to the two cases the Quick Start does not already cover, e.g. hom-ref and population-cohort composition) to remove the duplicated command sequence.

Merge the 'When to Use' bullet list and the 'Command Selection Guide' into a single question-to-command mapping, keeping the counting-first ordering in one place.

State the coordinate-verification rule once (in Coordinate Provenance, with the CAUTION box) and reference it from Core Rules and Common Mistakes instead of restating it three times.

DimensionReasoningScore

Conciseness

Nearly every token is service-specific knowledge Claude could not know (sentinel '-1' semantics, 'A zero numeric filter is unset on the server', pagination/RAM behavior, mutual-exclusivity rules, annotation-release caveats), with no explanation of concepts Claude already knows. Minor instances could be trimmed: the 'Typical Workflows' section repeats the Quick Start's identical command sequence with placeholders, the 'When to Use' bullet list and 'Command Selection Guide' both map questions to the same commands, and the coordinate-verification warning is stated three times (Core Rules, Coordinate Provenance, Common Mistakes). Efficient with minor trimmable redundancy — anchor 4 rather than 5.

4 / 5

Actionability

All guidance is executable: fully specified 'uv run scripts/onekgpd_api.py count-samples --chrom chr17 --start 43044295 --end 43170327 --consequence MISSENSE_VARIANT ...' commands with a complete worked Quick Start (real resolved BRCA1 coordinates, source URL, and retrieval tag), concrete meta-script invocations, and placeholder templates explicitly labeled 'replace all angle-bracket placeholders'. Nothing within the skill's scope is pseudocode — the one non-executable step (external coordinate resolution) is outside the skill's commands and is still concretely exemplified — so anchor 5 fits better than 4's 'minor gaps'.

5 / 5

Workflow Clarity

Multi-step processes are clearly sequenced with explicit validation checkpoints and feedback loops: mandatory coordinate resolution first, 'Call the count command FIRST to size the result set, then select only if the count is manageable', 'result_incomplete=true means results cannot support a definitive zero/absence claim. Re-run after service recovery', truncated-cap handling, and a Common Mistakes section with mistake→fix pairs. These are read-only queries, so the destructive/batch cap does not apply, and the count-first rule plus completeness checks constitute explicit validation — matching the anchor-5 feedback-loop pattern.

5 / 5

Progressive Disclosure

The body is a clear overview that keeps only summaries inline (command list, the 22 returned keys, filter-flag digest) and pushes full detail one level deep into two clearly signaled, purpose-described reference files — references/onekgpd_commands.md ('full per-command argument tables and the returned-variant output schema') and references/annotation_vocabularies.md ('the controlled-vocabulary terms accepted by the CSV filter flags') — both verified to exist with matching content. Scripts and the bundled offline data file (assets/kgpe.json, used by onekgpd_meta.py) are referenced by exact path. No nested references, no orphaned or buried content — anchor 5.

5 / 5

Total

19

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: third-person, concrete, and comprehensive, with an explicit 'Use when' trigger clause covering all four query classes and the returned annotation fields. The only weakness is that a handful of natural synonyms (kinship, carriers, 1KG) are absent.

Suggestions

Add a few natural synonyms users would say — e.g. 'kinship', 'carriers'/'who carries a variant', and the common '1KG' abbreviation for the cohort — to broaden trigger matching.

DimensionReasoningScore

Specificity

The description enumerates multiple concrete query classes — 'which individuals carry variants matching specific criteria in a gene or region', 'which individuals are homozygous-reference at a position', 'which variants exist in the dataset or carried by specified individuals', 'the relatedness between two specified individuals' — plus the returned data fields (KGP AF, gnomAD v4.1 exome/genome AF, AlphaMissense score, HGVSp). This matches the anchor 'lists multiple specific concrete actions; comprehensive coverage' of the skill's participant-level capabilities, rather than score 4's 'minor gaps in coverage'.

5 / 5

Completeness

It explicitly answers both parts: the 'what' ('Queries the 1000 Genomes Project dataset ... at the level of individual participants ... Variants are returned with 1000 Genomes allele frequencies (AF), gnomAD v4.1 exome and genome AF, AlphaMissense score, and HGVSp annotations') and the 'when' ('Use when a question is about individuals or variants in the 1000 Genomes Project cohort: ...'). This matches the anchor-5 example pattern exactly; score 4's 'when could be more explicit' does not apply since the trigger clause is fully explicit.

5 / 5

Trigger Term Quality

Good natural-term coverage: '1000 Genomes Project', 'individuals', 'variants', 'gene or region', 'homozygous-reference', 'relatedness', 'allele frequencies', 'gnomAD', 'AlphaMissense'. A few natural terms users would plausibly say are missing — 'kinship', 'carriers'/'carrier', and the common '1KG' abbreviation — placing it between the 'good coverage, a few natural terms missing' (4) and 'comprehensive synonyms' (5) anchors, closer to 4.

4 / 5

Distinctiveness Conflict Risk

The niche is unambiguous — a single named cohort ('the 1000 Genomes Project dataset (3,202 whole-genome-sequenced individuals, GRCh38)') at individual-participant level — and the trigger is scoped to 'a question is about individuals or variants in the 1000 Genomes Project cohort'. Clear niche with distinct triggers; minimal conflict risk with any other skill.

5 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
K-Dense-AI/scientific-agent-skills
Reviewed

Table of Contents

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