CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

tooluniverse-protein-structure-prediction

Protein 3D structure prediction from sequence — ESMFold de novo prediction, AlphaFold database retrieval, experimental structures from RCSB, ProtVar variant impact assessment, ProtParam sequence properties. Use for structure prediction when no experimental structure exists, fold-confidence scoring, and structure-guided variant interpretation.

Quality

86%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Medium

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Content

77%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.

An operationally excellent skill body: concrete tool contracts, calibrated quality thresholds, robust fallbacks, and a well-validated phase workflow. Its weaknesses are structural — redundant summary sections that repeat phase content, and a monolithic single-file layout with no progressive disclosure of the optional/advanced material (Boltz, DTU, parameter reference).

Suggestions

Remove or collapse the 'KEY PRINCIPLES' list and 'Databases Integrated' table — both restate content already covered by the phase sections and the tool reference, cutting ~40 lines of duplication.

Move the optional Boltz and DTU Health Tech sections into a references/ file (e.g., references/complex-and-membrane.md), keeping only a one-line pointer plus the cost-confirmation rule in SKILL.md so the core workflow loads lean.

Consolidate the repeated ESMFold ~800-residue limit into a single place (the fallback table or Limitations) instead of stating it in Phase 0, Phase 2, the fallback table, and Limitations.

DimensionReasoningScore

Conciseness

The body is dense with operational detail (parameters, thresholds, fallbacks), but includes unnecessary duplication: the 7-item "KEY PRINCIPLES" list restates the phase workflow that follows, "Databases Integrated" repeats tool info from each phase, and "Limitations" reiterates inline notes (e.g., the 800-residue limit appears in Phase 0, the fallback table, and Limitations). Not 4: the redundancy spans multiple sections, more than minor trimming; not 2: there is no concept padding or fluff — nearly all prose is operationally load-bearing.

3 / 5

Actionability

Fully concrete, executable guidance for an instruction-only skill: exact tool names with exact parameter names and aliases ("qualifier (or alias uniprot_id / uniprot_accession)"), value formats and examples ("P04637 R175H", "P00520"), calibrated interpretation tables (pLDDT/pTM ranges), and explicit decision logic. The scoring note about instruction-only skills applies — no code absence penalty; the guidance is copy-paste actionable.

5 / 5

Workflow Clarity

Clear Phase 0-6 sequence with per-phase objectives, a decision-logic section, a fallback strategies table (error recovery feedback loops), a "Quality Minimums" checklist for the final report, and an explicit validate-before-act checkpoint for the paid Boltz job ("Always estimate cost before submitting... confirm with the user"). Matches the anchor-5 pattern: explicit validation steps, feedback loops, and checklists for a complex process.

5 / 5

Progressive Disclosure

No bundle files exist and everything lives in one ~370-line SKILL.md. Section structure is clear (headers, tables, phase flow), but optional/advanced material that would naturally sit in separate reference files — the Boltz section, the DTU tools section, the Tool Parameter Reference, and the Databases Integrated table — is fully inlined. Matches anchor 3 ("some structure but... content that should be separate is inline"). Not 2: the structure is strong, not minimal, and nothing is deeply nested; not 4: no references are signaled at all, and the optional sections inflate the core file.

3 / 5

Total

16

/

20

Passed

Description

88%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.

A strong description: comprehensive, tool-specific capability list plus an explicit 'Use for' clause with concrete triggers. Minor losses come from a few missing natural phrasings (pLDDT, 'model') and slight semantic overlap with the sibling structure-retrieval skill.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions with named tools: "ESMFold de novo prediction, AlphaFold database retrieval, experimental structures from RCSB, ProtVar variant impact assessment, ProtParam sequence properties" — comprehensive coverage of the skill's capabilities. Not 4: no gaps in coverage; every capability in the body is named.

5 / 5

Completeness

Explicitly answers both: what — "Protein 3D structure prediction from sequence — ESMFold... ProtParam sequence properties"; when — "Use for structure prediction when no experimental structure exists, fold-confidence scoring, and structure-guided variant interpretation". Concrete trigger phrases in the 'when' clause match the anchor-5 example structure exactly.

5 / 5

Trigger Term Quality

Good natural keywords: "structure prediction", "no experimental structure exists", "fold-confidence scoring", "variant interpretation", "protein 3D structure". Not 5: a few natural user phrasings are missing ("pLDDT", "model this sequence", "predict the fold", " docking"). Not 3: synonyms like "fold" and "experimental structure" are present, so coverage goes beyond merely relevant.

4 / 5

Distinctiveness Conflict Risk

Clear niche (structure prediction from sequence) with distinct triggers, but "AlphaFold database retrieval, experimental structures from RCSB" overlaps semantically with the sibling retrieval skill (tooluniverse-protein-structure-retrieval, referenced in the body) — a retrieval-only request could route here. Not 5 for that overlap; not 3 since the prediction-centric triggers dominate and routing risk is minor.

4 / 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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

mims-harvard/ToolUniverse

Path

plugin/skills/tooluniverse-protein-structure-prediction/SKILL.md

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.