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tooluniverse-gpcr-structural-pharmacology

GPCR receptor pharmacology — agonist/antagonist/inverse-agonist/biased-agonist classification, GPCRdb structural data, receptor-ligand binding analysis, antibody-target interface (SAbDab). Use for GPCR drug discovery, biased-agonism analysis, receptor subtype selectivity questions, and orthosteric vs allosteric pocket characterization.

72

Quality

88%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

77%

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 with executable code and a well-sequenced workflow including checklists and fallbacks, but it is padded with domain concepts Claude already knows and is a monolithic single file rather than progressively disclosed across bundle files. Tightening the intro and splitting reference-style tables into separate files would lift the weakest dimensions.

Suggestions

Trim the opening pharmacology primer ('Biased agonism can separate efficacy from side effects; for example, G-protein-biased opioid agonists...') to a one-line directive, since Claude already knows GPCR signaling concepts.

Move the Tool Parameter Reference, Tool Combinations, Fallback Chains, and Key References tables into a separate references file (e.g. REFERENCE.md) and link to it from SKILL.md to avoid duplicating parameters across the table and per-phase code.

De-duplicate tool parameters that appear both in the reference table and inside the per-phase code comments, keeping the canonical spec in one place.

DimensionReasoningScore

Conciseness

Mostly efficient with executable code, but the opening paragraph explains pharmacology concepts Claude already knows (e.g. 'Biased agonism can separate efficacy from side effects') and tool parameters are restated in both the reference table and the per-phase code blocks. It is not a 3 because some padding and redundancy remain; not a 1 because the bulk is actionable, not conceptual filler.

2 / 3

Actionability

Each phase provides concrete, executable Python tool calls with real parameters and example values (e.g. GPCRdb_get_structures(protein="adrb2_human", state="inactive")), copy-paste ready rather than pseudocode.

3 / 3

Workflow Clarity

A clear five-phase sequence with a completeness checklist, explicit 'LOOK UP DON'T GUESS' checkpoint, and fallback chains for error recovery. It is not a 2 because checkpoints and fallbacks are explicit, not merely listed.

3 / 3

Progressive Disclosure

No bundle files exist (references/scripts/assets absent) and all ~290 lines live in one monolithic SKILL.md; sections like Tool Combinations, Fallback Chains, and Key References could be split out. It is not a 3 because at this length the single-file organization is more wall-of-text than well-signaled one-level references, and not a 1 because sections are clearly headed and navigable.

2 / 3

Total

10

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12

Passed

Description

100%

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 specific, third-person, and clearly answers both what the skill does and when to use it, with strong natural trigger terms for the GPCR structural pharmacology niche. No over-claims or vague fluff.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'agonist/antagonist/inverse-agonist/biased-agonist classification, GPCRdb structural data, receptor-ligand binding analysis, antibody-target interface (SAbDab)' — matching the 'lists multiple specific concrete actions' anchor.

3 / 3

Completeness

Explicitly answers both what (classification, structural data, binding analysis, antibody interface) and when via an explicit 'Use for GPCR drug discovery...' trigger clause, matching the top anchor.

3 / 3

Trigger Term Quality

Covers natural domain terms a user would say — 'GPCR drug discovery, biased-agonism analysis, receptor subtype selectivity questions, orthosteric vs allosteric pocket characterization' — giving good coverage rather than just technical jargon.

3 / 3

Distinctiveness Conflict Risk

A clear niche (GPCR structural pharmacology) with distinct, specialized triggers unlikely to overlap with generic skills. It is not a 2 because the triggers are domain-specific rather than generic.

3 / 3

Total

12

/

12

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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