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annotating-variants

Annotates VCF variants and normalizes HGVS nomenclature with public, license-free annotators (Ensembl VEP REST, VEP/SnpEff/ANNOVAR offline) and links variants to gnomAD population frequencies and the clinical context OpenMed extracts. Use when the user wants to predict variant consequences, map HGVS to genomic coordinates, annotate a VCF, attach allele frequencies, or pair variants with phenotype/oncology context. Trigger keywords: VCF, HGVS, variant annotation, VEP, SnpEff, ANNOVAR, consequence, missense, gnomAD, allele frequency, GRCh38, rsID, transcript. Pairs adjacent to OpenMed: combine annotated variants with Genomics/Oncology entities and phenotype from openmed.analyze_text. Tools used are free; restricted clinical databases are user-supplied.

69

Quality

87%

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SKILL.md
Quality
Evals
Security

Quality

Content

68%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 strong, dense body: executable REST and GraphQL code with real examples, genuinely non-obvious gotchas, and clean sectioning. The main gaps are the absence of validation/verification checkpoints in the batch-annotation workflow (capping workflow clarity at 3) and the offline-tool path being named but not commandable, with everything inlined in one file rather than split across references.

Suggestions

Add validation checkpoints to the Workflow section for batch jobs, e.g. after annotating a whole VCF verify that every input variant produced a record (report and retry dropped/failed variants, honor Retry-After on 429) before moving to frequency attachment — this lifts workflow_clarity past its batch-operation cap of 3.

Make the offline path executable: include one concrete command per tool (e.g. `vep --cache --offline --fasta <genome.fa> -i input.vcf` and the equivalent `SnpEff`/`table_annovar.pl` invocations) instead of a strengths/notes table, since actionability currently rests entirely on the REST examples.

Move the gnomAD GraphQL query details and the edge-cases material into reference files (e.g. references/gnomad.md, references/gotchas.md) with one-line pointers from SKILL.md, trimming the body toward an overview and reducing redundancy between the intro, "When to use", and the frontmatter description.

DimensionReasoningScore

Conciseness

The body is lean and assumes competence — no "what is a VCF" filler, and the gotchas are genuinely non-obvious domain knowledge (build mismatch, gnomAD ac/an schema quirks, transcript pinning). It falls short of anchor 5 because of minor redundancy: the "When to use" section restates the frontmatter description's triggers, and the intro paragraph repeats it again, so a few tokens could be trimmed without losing anything.

4 / 5

Actionability

The REST path is fully executable and copy-paste ready — `vep_hgvs("ENST00000269305.9:c.215C>G")` with a real TP53 example, the batch POST with the exact region format, a cURL equivalent, and a working gnomAD GraphQL query — which is anchor-5 material. It stays at 4 because the offline-at-scale path is descriptive only: the VEP/SnpEff/ANNOVAR table names tools and strengths but provides no concrete command (e.g. a `vep --cache` invocation), leaving that half of the skill non-executable as written.

4 / 5

Workflow Clarity

The 5-step Workflow is clearly sequenced (normalize → annotate → attach frequencies → filter → join to context), but it contains no validation or verification checkpoints despite the skill explicitly describing batch operations ("Batch many variants with the POST endpoint", "For whole-VCF jobs"). Per the rubric's guideline that batch workflows missing validation cap at 3, this fits anchor 3 ("sequence present but checkpoints missing or implicit") — the edge-cases section gestures at error handling (Retry-After on 429) but there is no validate-and-retry loop in the workflow itself, which is what anchor 4+ requires.

3 / 5

Progressive Disclosure

The single-file body is well organized with clearly signaled sections and a "Standards & references" list of external links, and no bundle files exist so nothing is misfiled. It does not reach 5 because everything is inlined in one ~170-line file: the gnomAD GraphQL details and the offline-annotation guidance are secondary-depth material that a reference file could hold, and the guideline's 5-with-sections-only allowance applies to skills under 50 lines, which this exceeds. It sits above 3 because the structure is clean and nothing is buried.

4 / 5

Total

15

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20

Passed

Description

100%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.

An excellent description: concrete third-person actions, an explicit 'Use when' clause with specific triggers, comprehensive natural keywords, and a well-delineated niche with explicit adjacency to OpenMed. The only minor weakness is padding in the tail (licensing notes and OpenMed pairing detail) that adds length without adding triggering value, but it does not drop any dimension below its top anchor.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — "Annotates VCF variants", "normalizes HGVS nomenclature", "links variants to gnomAD population frequencies", "pair variants with phenotype/oncology context" — and names the exact tools (Ensembl VEP REST, VEP/SnpEff/ANNOVAR offline). Coverage is comprehensive across the skill's capabilities, matching the anchor-5 example's breadth; it is not the anchor-4 case because there are no noticeable coverage gaps.

5 / 5

Completeness

It explicitly answers both questions: "what" ("Annotates VCF variants and normalizes HGVS nomenclature... links variants to gnomAD population frequencies") and "when" ("Use when the user wants to predict variant consequences, map HGVS to genomic coordinates, annotate a VCF, attach allele frequencies, or pair variants with phenotype/oncology context"). This mirrors the anchor-5 good_overall_example structure exactly; a 4 would require the 'when' clause to be less explicit, which it is not.

5 / 5

Trigger Term Quality

The trigger list — VCF, HGVS, variant annotation, VEP, SnpEff, ANNOVAR, consequence, missense, gnomAD, allele frequency, GRCh38, rsID, transcript — comprehensively covers the natural terms a user would say, including tool names, file formats, and domain synonyms. It matches the anchor-5 pattern (cf. "PDF files, PDFs, forms, document extraction, .pdf") rather than the anchor-4 case of a few missing natural terms.

5 / 5

Distinctiveness Conflict Risk

It carves a clear niche — variant annotation with named annotators and gnomAD frequency linking — with distinct trigger terms (HGVS, VEP, SnpEff, rsID) that no adjacent generic genomics skill would claim. Explicitly scoping the OpenMed relationship ("Pairs adjacent to OpenMed") further reduces overlap risk, fitting anchor 5's "clear niche with distinct triggers; minimal conflict risk".

5 / 5

Total

20

/

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

maziyarpanahi/openmed

Path

skills/annotating-variants/SKILL.md

Reviewed

Table of Contents

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