AB variant-annotation
Query and annotate gene variants from ClinVar and dbSNP databases. Trigger when: - User provides a variant identifier (rsID, HGVS notation, genomic coordinates) and asks about clinical significance - User mentions "ClinVar", "dbSNP", "variant annotation", "pathogenicity", "clinical significance" - User wants to know if a mutation is pathogenic, benign, or of uncertain significance - User provides VCF content or variant data requiring interpretation - Input: variant ID (rs12345), HGVS notation (NM_007294.3:c.5096G>A), or genomic coordinates (chr17:43094692:G>A) - Output: clinical significance, ACMG classification, allele frequency, disease associations
As a process B 66/100 · Nearly there — weak spots: consistency, running it twice, progress reporting
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 660 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - note
frontmatter-keyunknown frontmatter key "status" - note
frontmatter-keyunknown frontmatter key "risk_level" - note
frontmatter-keyunknown frontmatter key "skill_type" - note
frontmatter-keyunknown frontmatter key "owner" - note
frontmatter-keyunknown frontmatter key "reviewer" - note
frontmatter-keyunknown frontmatter key "last_updated"
Process rating: all ten parameters 66/100
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (variant-annotation) differs from the folder (variant-annotation-2)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 75 steps
- 100Execution cost. Instruction body is 2220 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 16 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- -44 reference files, but SKILL.md never points to them: the model will not open them
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 660: enough signal without eating the budget
- +4Structure: 24 headings
- +3Step-by-step instructions: 75 items
- +3Output format is stated explicitly
- +4Has examples (4 code blocks)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.