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proteinmpnn

Design protein sequences from fixed backbone structures with ProteinMPNN-style workflows. Use when a task asks for backbone-conditioned sequence design, mutation suggestions, fixed residues, or design filtering.

68

Quality

81%

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SecuritybySnyk

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 content is concise and well-structured for a small instruction-only skill, with a clear sequenced workflow. Its main weakness is actionability: it stays at the level of directives rather than giving the concrete commands or ProteinMPNN flags needed to execute each step.

Suggestions

Add a concrete runnable example or the key ProteinMPNN command/flags for fixed and tied residues so step 1-4 are executable, not just descriptive.

Expand the design-filtering step with an explicit validation/feedback loop (e.g., re-predict structure, check diversity, retry on failure) since it is a batch operation.

Specify what 'verify the local or remote execution route' means concretely — the command or check to run — rather than leaving it as a directive.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence — it never explains what ProteinMPNN or a backbone is, and every line earns its place within ~13 lines.

5 / 5

Actionability

Guidance is high-level and abstract ('Verify the local or remote execution route', 'Filter designs by constraints') with no concrete commands, flags, or a runnable ProteinMPNN invocation for tied/fixed positions; it describes more than it instructs.

2 / 5

Workflow Clarity

A clear five-step sequence is present with verification built into steps 2 and 5, but the filtering step (a batch operation) lacks an explicit validate-fix-retry feedback loop, leaving a minor validation gap.

4 / 5

Progressive Disclosure

At under 50 lines with no need for external references, the well-organized intro-plus-numbered-workflow structure meets the simple-skill exception for a top progressive-disclosure score.

5 / 5

Total

16

/

20

Passed

Description

92%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 strong: it pairs a concrete capability statement with an explicit, trigger-rich 'Use when' clause in third person. Minor gains would come from adding common synonyms and file extensions like .pdb and mmCIF.

Suggestions

Add common synonyms and file extensions (e.g., '.pdb', 'mmCIF', 'sequence recovery') to the trigger clause to improve trigger-term coverage.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Design protein sequences', 'fixed backbone structures', 'mutation suggestions', 'fixed residues', 'design filtering' — giving comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

It clearly states what the skill does ('Design protein sequences from fixed backbone structures...') and explicitly when to use it ('Use when a task asks for...') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Natural triggers like 'backbone-conditioned sequence design', 'mutation suggestions', and 'fixed residues' are present, but common synonyms and file extensions (e.g. .pdb, mmCIF) that users would mention are missing.

4 / 5

Distinctiveness Conflict Risk

The ProteinMPNN / fixed-backbone niche is clearly scoped with distinct triggers, making conflict with other skills unlikely.

5 / 5

Total

19

/

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
companion-inc/feynman
Reviewed

Table of Contents

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