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boltz-protein-screen

Screen existing protein binders with Boltz. Use when ranking a supplied protein, peptide, antibody, nanobody, or binder library against a target. Not for designing new proteins or screening small molecules.

72

Quality

88%

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SecuritybySnyk

Critical

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SKILL.md
Quality
Evals
Security

Quality

Content

91%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 skill body is a strong, executable runbook: a numbered workflow with validation gates, complete command patterns, and clean one-level-deep references that are confirmed to exist. The main opportunity is tightening the somewhat repetitive runtime-specific (Claude Code vs Codex) guidance across the workflow and 'Always Do This' sections.

Suggestions

Consolidate the repeated Claude Code vs Codex background-launch instructions (currently stated in steps 6, the command comments, and several 'Always Do This' bullets) into a single canonical block to reduce redundancy.

Consider moving the longer runtime-specific heartbeat guidance for Codex app/desktop into references/ to keep the SKILL.md overview tighter while preserving the detail.

Trim restated flag guidance (e.g. idempotency-key/workspace-id precedence) that already appears in references/api.md to avoid duplication.

DimensionReasoningScore

Conciseness

The body is largely lean and assumes Claude's competence with concrete commands and flags, though the repeated Claude Code / Codex runtime distinctions and long 'Always Do This' bullets introduce some redundancy that could be tightened.

4 / 5

Actionability

Provides copy-paste-ready executable command blocks with concrete flags, placeholders clearly marked, and specific run-time invocation instructions for both Claude Code and Codex, covering the common cases.

5 / 5

Workflow Clarity

A clearly numbered 7-step workflow is sequenced with explicit validation checkpoints — estimate-cost then wait for explicit confirmation before start, capture the ID, launch download non-blocking, then rank — plus recovery guidance for restarts and auth failures.

5 / 5

Progressive Disclosure

SKILL.md is a concise overview with well-signaled one-level-deep references (references/api.md and references/results.md), and both referenced files exist in the bundle, keeping the split appropriately shallow and navigable.

5 / 5

Total

19

/

20

Passed

Description

86%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 well-constructed: it states a concrete capability, gives explicit 'Use when' trigger guidance with concrete input types, and sharply scopes boundaries. It is concise and avoids fluff. Minor additional natural synonyms could lift trigger term quality to fully comprehensive.

DimensionReasoningScore

Specificity

Names the concrete action ('Screen existing protein binders with Boltz') and enumerates the input types (protein, peptide, antibody, nanobody, binder library), but stops short of listing multiple distinct concrete actions like ranking or cost estimation.

4 / 5

Completeness

Explicitly answers 'what' ('Screen existing protein binders with Boltz') and 'when' ('Use when ranking a supplied protein... against a target') with concrete trigger phrasing, plus a clear out-of-scope statement.

5 / 5

Trigger Term Quality

Includes natural user-facing terms like 'protein binders', 'antibody', 'nanobody', and 'binder library' plus the target concept, but misses a few common synonyms or file extensions a user might mention.

4 / 5

Distinctiveness Conflict Risk

The combination of binder-library screening plus an explicit 'Not for designing new proteins or screening small molecules' carve-out gives it a clear niche with minimal conflict risk against adjacent skills.

5 / 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
openai/plugins
Reviewed

Table of Contents

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