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tooluniverse-hla-immunogenomics

HLA gene-family analysis and MHC-peptide binding for transplant compatibility, vaccine epitope coverage, and cancer immunotherapy. Uses IMGT (HLA polymorphism), IEDB (epitope-MHC binding), UniProt (annotation), DGIdb (druggability). Use for HLA typing/imputation review, vaccine HLA coverage, and immunotherapy prediction biomarkers (HLA-LOH, neoantigen presentation).

68

Quality

81%

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SKILL.md
Quality
Evals
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Quality

Content

75%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-structured, actionable immunogenomics analysis skill with a clear phased workflow and concrete tool guidance. The main gaps are some over-explained background immunology and the absence of an example for its own "write and run Python" directive.

Suggestions

Trim the Reasoning Strategy paragraph: drop the HLA-B27/abacavir/class-I-vs-II background that Claude already knows, keeping only the LOOK-UP-DON'T-GUESS directives and guiding principles.

Add one short copy-paste Python snippet under "COMPUTE, DON'T DESCRIBE" (e.g., loading IEDB/IMGT tool results into a pandas DataFrame for binding-affinity ranking) so the directive is immediately actionable.

Insert lightweight validation checkpoints between phases (e.g., after Phase 1/2, confirm the allele and binding data are non-empty and species-matched before proceeding) to raise workflow clarity.

DimensionReasoningScore

Conciseness

Mostly efficient with concrete tool specs and thresholds, but the Reasoning Strategy paragraph re-explains known immunology (HLA-B27/ankylosing spondylitis, abacavir/HLA-B*57:01, class I vs II biology) that could be trimmed.

4 / 5

Actionability

Provides concrete tool names with explicit inputs/outputs and binding-affinity thresholds (IC50 < 50 nM strong), but the "COMPUTE, DON'T DESCRIBE" directive urging Python execution gives no runnable example to follow.

4 / 5

Workflow Clarity

A clear 7-phase pipeline with ASCII flow, per-phase tools and workflows, plus recovery notes ("If allele not found: Check nomenclature"), though it lacks explicit inter-phase validation/checkpoint feedback loops.

4 / 5

Progressive Disclosure

Well-organized single-file skill with clear section headers and navigation, no nested references; the substantial inlined phase-detail content is the only thing keeping it from a 5 for a no-bundle skill.

4 / 5

Total

16

/

20

Passed

Description

88%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, specific description that concretely states capabilities and explicit use-trigger phrases, covering the HLA/immunogenomics niche well. Slightly technical in trigger terms and has minor overlap risk with a sibling immunotherapy skill.

DimensionReasoningScore

Specificity

Lists multiple concrete actions and domains — "HLA gene-family analysis and MHC-peptide binding", "transplant compatibility, vaccine epitope coverage, and cancer immunotherapy" — giving comprehensive coverage rather than just 1-2 actions.

5 / 5

Completeness

Explicitly answers both what ("HLA gene-family analysis and MHC-peptide binding...") and when ("Use for HLA typing/imputation review, vaccine HLA coverage...") with concrete trigger phrases.

5 / 5

Trigger Term Quality

Good coverage of natural in-domain terms ("HLA typing", "vaccine HLA coverage", "MHC-peptide binding", "epitope"), but lacks lay synonyms or file-extension variants that would push it to comprehensive.

4 / 5

Distinctiveness Conflict Risk

Clearly a distinct HLA/immunogenomics niche with specific triggers, but the body acknowledges a closely-related sibling skill (tooluniverse-immunotherapy-response-prediction), indicating minor overlap risk rather than minimal.

4 / 5

Total

18

/

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
mims-harvard/ToolUniverse
Reviewed

Table of Contents

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