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tooluniverse-structural-proteomics

Structural biology plus proteomics integration for drug target validation. Combines PDB experimental structures, AlphaFold predictions, GPCRdb, SAbDab antibody structures, ProteinsPlus binding-site prediction, BindingDB ligand-affinity data, BMRB NMR data, CATH/InterPro fold classification, intrinsic-disorder prediction (MobiDB/DisProt/IUPred3), membrane-protein topology (OPM/TopDB/PDBTM/ChannelsDB), enzyme catalytic-site data (M-CSA), PDBe ligand/compound chemistry, and MD simulation trajectory metadata (MDDB). Use for druggability assessment, binding-site characterization, ligand-pocket analysis, structural-confidence scoring (resolution, pLDDT), antibody-target interface analysis, disordered-region assessment, membrane-protein topology, catalytic-mechanism lookup, and finding published MD simulations for a target.

Quality

88%

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Passed

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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.

The body is a dense, highly actionable reference with real verified tool behavior that Claude could not infer — its greatest strength — but it is a monolithic 317-line file with no progressive disclosure, systematically repeated gotchas, and verbose narrative examples. Actionability is top-tier; conciseness and file structure are the clear improvement areas.

Suggestions

Deduplicate the gotchas: state each once in its workflow (or once in the Gotchas table) instead of the current threefold repetition of PDBe_get_compound_structures, MobiDB unreachability, and InterPro flakiness across workflow, table, and Limitations sections.

Move the Tool Inventory section (~55 lines of tool signatures) into a references/tool-inventory.md file and keep SKILL.md to workflows, decision rules, and interpretation tables, cutting the main file roughly in half.

Tighten the 'Real example' narratives to the call plus the key output fields (e.g. reduce the MDDB example to the tool call, project accession, and one-line result), since the extended parameter dumps repeat information already in the tool inventory.

DimensionReasoningScore

Conciseness

The body mostly earns its tokens with verified-live tool behaviors Claude cannot know (parameter gotchas, the MobiDB endpoint hang, the PDBe_get_compound_structures fallback), but several gotchas are stated three times each (compound_structures in Workflow 2, the Gotchas table, and Limitations; likewise MobiDB unreachability and InterPro flakiness), and the 'Real example' narratives run long (e.g. the full MDDB parameter dump for MD-A001UA). This is 'mostly efficient but includes some unnecessary explanation or could be tightened' — beyond the score-4 anchor's 'minor instances', but well short of the severe padding of score 2.

3 / 5

Actionability

Guidance is fully executable: exact tool names with parameter signatures ("alphafold_get_prediction (qualifier=UniProt)"), copy-paste-ready verified calls with real arguments and outputs ("InterPro_get_member_signature(member_database='pfam', accession='PF00069')"), and a Mistake/Correct gotcha table. Specific examples cover the common cases (kinases, p53, rhodopsin, lysozyme, ubiquitin, ATP/HEM), matching the score-5 anchor; it does not fall to score 4 because no execution gaps remain for an agent with these tools.

5 / 5

Workflow Clarity

The nine workflows are clearly phased with tool-per-phase sequences, and several include explicit validation checkpoints ("PDBeValidation quality → binding site well-resolved?", BMRB_get_validation gating shift trust) plus a retry feedback loop for the flaky InterPro endpoints. However, checkpoints are uneven — Workflows 1-3 phases are terse one-liners ('Phase 8: Evidence integration') with implicit validation — so it fits 'Clear sequence with most checkpoints present; minor validation gaps' rather than the score-5 anchor requiring explicit validation and feedback loops throughout.

4 / 5

Progressive Disclosure

The section structure is good (LOOK UP DON'T GUESS, tool inventory, workflows, gotchas, evidence grading, limitations), but the skill is a 317-line monolith with zero reference files: the ~55-line tool inventory and the long verified-example narratives are exactly the content the rubric says belongs in a separate references/ file. This matches 'Some structure... content that should be separate is inline' rather than score 4 ('most content is appropriately placed'), since nothing is split out at all; it stays above score 2 because internal headers make navigation genuinely easy.

3 / 5

Total

15

/

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 exemplary: third-person, specific, and comprehensive, with a dense enumeration of concrete capabilities and an explicit 'Use for...' trigger clause covering nine distinct use cases. Every dimension lands on its top anchor; the only minor criticism is length, but each phrase carries capability information rather than padding.

DimensionReasoningScore

Specificity

The description lists many concrete capabilities across named sources ("ProteinsPlus binding-site prediction, BindingDB ligand-affinity data, BMRB NMR data, CATH/InterPro fold classification, intrinsic-disorder prediction (MobiDB/DisProt/IUPred3), membrane-protein topology (OPM/TopDB/PDBTM/ChannelsDB), enzyme catalytic-site data (M-CSA)") plus concrete actions ("druggability assessment, binding-site characterization, ligand-pocket analysis, structural-confidence scoring (resolution, pLDDT)"). Coverage is comprehensive with no generic filler, matching the anchor 'Lists multiple specific concrete actions; comprehensive coverage' rather than the score-4 anchor, which expects minor gaps.

5 / 5

Completeness

It explicitly answers both questions: the 'what' is the opening integration statement ("Structural biology plus proteomics integration for drug target validation. Combines PDB experimental structures, AlphaFold predictions...") and the 'when' is an explicit 'Use for...' clause with concrete trigger cases. This matches the score-5 anchor exactly; the score-4 anchor's weaker 'when' does not apply.

5 / 5

Trigger Term Quality

Natural domain terms and their synonyms appear densely: "druggability assessment", "binding-site characterization", "ligand-pocket analysis", "antibody-target interface analysis", "disordered-region assessment", "membrane-protein topology", "catalytic-mechanism lookup", "finding published MD simulations", plus database names (PDB, AlphaFold, GPCRdb, SAbDab) users would naturally mention. This matches 'Comprehensive coverage of natural terms including synonyms' (file extensions are inapplicable to this domain); it is well above the score-4 anchor's 'a few natural terms missing'.

5 / 5

Distinctiveness Conflict Risk

A clear niche (structural proteomics for drug target validation) with highly specific triggers tied to named databases and analysis types. Overlap risk with other skills is minimal — no other plausible skill would claim these triggers — fitting 'Clear niche with distinct triggers; minimal conflict risk' rather than the score-4 anchor's 'minor overlap risk with closely related 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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

mims-harvard/ToolUniverse

Path

plugin/skills/tooluniverse-structural-proteomics/SKILL.md

Reviewed

Table of Contents

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