CtrlK
BlogDocsLog inGet started
Tessl Logo

tooluniverse-immunology

Immunology research workflows: antibody-antigen interactions, T/B cell repertoire, MHC/HLA binding prediction, autoimmune disease genetics, vaccine epitope mapping. Uses IEDB, IMGT, SAbDab, UniProt. Use for adaptive immunity questions, immune response analysis, antibody/TCR/BCR characterization, immunogenicity prediction, and immune-pathway-to-disease mapping.

74

Quality

91%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

82%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.

The body is highly actionable — concrete tool signatures, exact IDs, and a parameter-gotchas table — with clear sequenced workflows. Its main weakness is mild verbosity in the conceptual Reasoning Frameworks section and a long inline tool reference that could be split out for tighter progressive disclosure.

Suggestions

Trim the Reasoning Frameworks section to immunology-specific decision rules and move general concepts (innate vs adaptive timing, basic complement biology) that Claude already knows into a reference file or remove them.

Consider extracting the dense Tool Reference tables into a references/ file (e.g. tool-reference.md) and keeping only the most-used tools inline, improving progressive disclosure and token efficiency.

Add explicit validation/retry checkpoints to the Workflows (e.g. 'verify epitope hits via a second IEDB assay type before proceeding') so multi-step research paths have clear feedback loops.

DimensionReasoningScore

Conciseness

The bulk is genuinely novel tool/parameter/ID knowledge (gotchas table, pathway IDs, exact accession formats) that earns its place, but the Reasoning Frameworks section restates general immunology concepts (innate vs adaptive, complement pathways) Claude largely already knows, leaving minor instances of over-explanation to trim.

4 / 5

Actionability

Tool names, exact parameter names, literal example values ('hsa04630', 'Q9NZQ7', 'stId='), and a wrong/correct Parameter Gotchas table provide copy-paste-ready, fully executable guidance covering the common cases.

5 / 5

Workflow Clarity

The Workflows section gives clearly sequenced tool chains and the Evidence Grading section acts as a soft validation checkpoint, but explicit verify/retry feedback loops are largely implicit rather than spelled out, placing it just below the anchor-5 bar.

4 / 5

Progressive Disclosure

Single-file skill with clean, navigable section structure (LOOK UP, COMPUTE, Reasoning Frameworks, Tool Reference, Gotchas, Workflows); at ~150 lines the long inline Tool Reference could arguably live in a separate reference file, so it does not reach the anchor-5 ideal.

4 / 5

Total

17

/

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.

The description is comprehensive and well-constructed: it states concrete capabilities, includes a clear 'Use for...' trigger clause, and occupies a distinct immunology niche with low conflict risk. Voice is correctly third person throughout.

DimensionReasoningScore

Specificity

Lists multiple concrete capabilities — 'antibody-antigen interactions, T/B cell repertoire, MHC/HLA binding prediction, autoimmune disease genetics, vaccine epitope mapping' plus characterization and immunogenicity prediction — matching the comprehensive-coverage anchor 5 rather than anchor 4 which requires minor gaps.

5 / 5

Completeness

Explicitly states the 'what' (research workflows and listed tasks) and the 'when' via an explicit 'Use for adaptive immunity questions, immune response analysis...' trigger clause, satisfying the anchor-5 requirement for both with concrete trigger phrases.

5 / 5

Trigger Term Quality

Natural user-facing phrases like 'adaptive immunity questions', 'immune response analysis', 'antibody/TCR/BCR characterization', and 'vaccine epitope mapping' give comprehensive coverage of how a user would actually phrase the need.

5 / 5

Distinctiveness Conflict Risk

The immunology niche and domain-specific triggers (MHC/HLA binding, epitope mapping, IEDB/IMGT/SAbDab) create a clear niche with minimal overlap risk against other skills.

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
mims-harvard/ToolUniverse
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.