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tooluniverse-rare-disease-genomics

Rare disease genomics — disease identification (Orphanet), causative gene discovery, gene-disease validity (GenCC), variant interpretation (ClinVar), and translational research (ClinicalTrials.gov, drug repurposing for orphans). Use for rare-disease-gene curation, novel-gene-discovery analysis, and rare-disease drug-development support.

63

Quality

75%

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tessl review fix ./plugins/tooluniverse/skills/tooluniverse-rare-disease-genomics/SKILL.md

The canonical home for this skill is tooluniverse-rare-disease-genomics in mims-harvard/ToolUniverse

SKILL.md
Quality
Evals
Security

Quality

Content

71%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, information-dense orchestration skill: exact tool parameters, explicit sequencing, evidence tiers, and a completeness checklist make it highly actionable. Its weaknesses are the absence of any progressive disclosure (the full API reference is inlined in a ~280-line monolith with no bundle files), minor token padding (basic genetics, chatty asides), one incoherent self-referential fallback bullet, and no runnable Python example despite the compute-first directive.

Suggestions

Move the per-tool parameter reference (Phases 0-8 tool blocks) into a references/ file (e.g., references/tool-reference.md), keeping SKILL.md as the workflow overview with clearly signaled one-level-deep pointers per phase.

Fix the self-referential fallback bullet 'Disease lookup: try `Orphanet_search_diseases` if `Orphanet_search_diseases` fails' — presumably it should name a different tool such as `Orphadata_search_by_name`.

Trim the basic inheritance-mode explanations and the deep-intronic digression to one-line pointers, and add one small runnable Python example (e.g., a pandas merge of Orphanet genes with GenCC classifications) to back the 'COMPUTE, DON'T DESCRIBE' directive.

DimensionReasoningScore

Conciseness

The body is dense with non-redundant, database-specific guidance ('The parameter is `name` (NOT `query`)', 'Check `len(studies) > 0` rather than `total_count`'), but includes trimmable over-explanation: basic inheritance-mode genetics Claude already knows ('Autosomal recessive: need TWO hits (homozygous or compound heterozygous)') and a chatty multi-clause aside on deep intronic variants ("but 'usually' is doing real work"). This matches 'efficient; minor instances of over-explanation that could be trimmed' rather than 5, whose every-token-earns-its-place bar the padded asides miss, and rather than 3, since the over-explanation is minor relative to the parameter-level detail Claude cannot know.

4 / 5

Actionability

Every tool has exact required parameters and types ('Orphanet_get_disease: `orpha_code` (string REQUIRED, e.g., "558")') and the example workflows give concrete calls ('Orphanet_search_diseases(name="Marfan syndrome") -> ORPHAcode 558'), but the workflows use `->` shorthand rather than copy-paste code and no runnable Python analysis example appears despite the 'COMPUTE, DON'T DESCRIBE' directive. This is 'mostly executable guidance with minor gaps' — not 5 (not fully copy-paste ready), not 3 (the tool calls are concrete and specific, not pseudocode).

4 / 5

Workflow Clarity

Phases 0-9 are explicitly sequenced with an ordering rule ('phenotype -> disease -> gene -> variant, not the reverse'), evidence-grading tiers, a completeness checklist, and a fallback/error-recovery section. It falls short of 5 because one fallback bullet is self-referential and incoherent ('Disease lookup: try `Orphanet_search_diseases` if `Orphanet_search_diseases` fails') and per-phase exit criteria are sometimes implicit; it is above 3 because the checklist, tiering, and fallbacks provide real validation checkpoints. The destructive/batch cap does not apply — this is read-only research orchestration.

4 / 5

Progressive Disclosure

No bundle files exist (no references/, scripts/, or assets/ directories), so the entire ~280-line per-tool API reference is inlined in SKILL.md and loads on every invocation. Section headers are clear (one section per phase), which keeps it above 2 ('minimal structure'), but bulk parameter reference that clearly belongs in a separate reference file is inline with no one-level-deep pointers, matching 'some structure... content that should be separate is inline' rather than 4.

3 / 5

Total

15

/

20

Passed

Description

80%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: it enumerates five concrete capabilities tied to specific databases and gives an explicit 'Use for...' clause, so both what and when are answered with high specificity and a clear niche. The main gap is trigger phrasing — the when-clause uses curator-style compound jargon rather than the natural words users would say, leaving a few natural terms and synonyms missing.

DimensionReasoningScore

Specificity

The description lists five concrete capabilities each anchored to a named resource — 'disease identification (Orphanet), causative gene discovery, gene-disease validity (GenCC), variant interpretation (ClinVar), and translational research (ClinicalTrials.gov, drug repurposing for orphans)' — which matches 'lists multiple specific concrete actions; comprehensive coverage'. It is not 4: the enumeration spans the full workflow from disease to drug development with no notable coverage gap, and all actions are concrete rather than generic.

5 / 5

Completeness

Both parts are explicit: a clear 'what' (five enumerated capabilities) and an explicit when-clause ('Use for rare-disease-gene curation, novel-gene-discovery analysis, and rare-disease drug-development support'). It falls just short of 5 because the trigger phrases are formal compound terms rather than the concrete, natural user phrasings the top anchor requires ('when the user mentions PDFs, forms, or document extraction'), and is clearly above 3 since the when-guidance is explicit, not merely implied.

4 / 5

Trigger Term Quality

Natural terms like 'rare disease', 'variant interpretation', and 'drug repurposing' are present, but the when-clause leans on compound jargon ('rare-disease-gene curation, novel-gene-discovery analysis') rather than phrases users naturally say, and common synonyms ('orphan disease', 'inherited disorder', 'genetic disorder') are absent from the description. This sits between anchor 3 and anchor 5, landing at 'good keyword coverage; a few natural terms missing' — not 5 because synonyms and natural user phrasings are missing, not 3 because genuinely natural keywords are included.

4 / 5

Distinctiveness Conflict Risk

The description carves a clear niche via named resources (Orphanet, GenCC, ClinVar) and scoping to rare disease, matching 'mostly distinct; minor overlap risk with closely related skills'. It is not 5 because the skill family it belongs to has close siblings (differential diagnosis, pharmacogenomics, cancer variant interpretation) whose territory shares terms like 'variant interpretation' and 'gene-disease', and not 3 because the rare-disease genomics niche and its database anchors are unmistakable.

4 / 5

Total

17

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
mims-harvard/ToolUniverse
Reviewed

Table of Contents

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