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pdb-database

Use when you want to search for or download experimentally-determined 3D structures for biomolecules (proteins, nucleic acids, bound ligands). Supports searching by sequence similarity, structure similarity, chemical and other attributes. Also use to get metadata about biomolecular structure experiments.

Quality

88%

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SKILL.md
Quality
Evals
Security

Quality

Content

82%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.

A highly actionable, well-structured body: every workflow is backed by real, copy-paste-ready script commands, and the domain knowledge included (label vs auth, entity vs assembly) is genuinely non-obvious and tied to attribute choice. The main gaps are the absence of explicit verification/error-recovery steps in the workflows, a few concept entries that restate common knowledge, and an orphaned references/citation.bib that the body never points to.

Suggestions

Add a brief verification step to the search and download workflows (e.g., check results.json hit count with `--count_only` before fetching, and confirm expected files landed in OUTPUT_DIR, retrying/reporting failed IDs).

Either link references/citation.bib from the body (e.g., under Prerequisites or a References section) or remove it, so the bundle has no orphaned files.

Trim the concept glossary entries that restate widely known facts (Entity, Resolution) and keep only the PDB-specific distinctions (label vs auth, instance vs entity, assembly) to tighten token usage.

DimensionReasoningScore

Conciseness

The body is lean and command-driven — mostly executable `uv run` invocations, operator lists, and API-specific gotchas (label vs auth, entity vs instance) that Claude genuinely does not know, matching anchor 4 rather than 5. A few concept entries lean on knowledge Claude partly has (e.g. "Resolution: Frequently used measure of structure quality (lower is better)", "Entity: A unique molecule found in a structure") and could be trimmed, but there is no padding and no generic-library tutorializing that would justify 3 or lower.

4 / 5

Actionability

Every workflow gives complete, copy-paste-ready `uv run scripts/... --query '<full JSON/GraphQL>'` commands, and all four referenced scripts actually exist in scripts/. The examples span the common cases (attribute search with sort/count options, sequence, structure, motif, chemical-descriptor, full-text, batch download, GraphQL metadata), matching anchor 5 ("fully executable; copy-paste ready; specific examples cover the common cases").

5 / 5

Workflow Clarity

Each workflow is a clearly numbered sequence (fetch schema → grep schema → compose query; and equivalents for metadata), with soft checkpoints like "examine many lines... choose the best match", the `--count_only` sanity-check flag, and the core rule to explain queries so the user can correct bad assumptions; the provided scripts also embed rate limiting, per-file error handling, and a bulk-abort check. It falls short of anchor 5 because the body has no explicit result-verification or error-recovery step (e.g., checking results.json for zero hits, or what to do when a download fails), keeping it at anchor 4 ("clear sequence with most checkpoints present; minor validation gaps") rather than triggering the batch cap at 3, since downloads are non-destructive and failure handling is embedded in the script.

4 / 5

Progressive Disclosure

The body is well-sectioned (Prerequisites, Core Rules, then one section per workflow), all script references are one level deep and resolve to real files, and executable code is appropriately pushed into scripts/ rather than inlined. It is not a 5: references/citation.bib exists in the bundle but is never linked or signaled from the body (an orphaned, undiscoverable reference), and the sizable inline concept glossary and example-query blocks are candidates for a references/ file, matching anchor 4 ("good structure... minor organization gaps").

4 / 5

Total

17

/

20

Passed

Description

87%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 that explicitly covers what the skill does (search, download, metadata across attribute/sequence/structure/chemical modes) and when to use it, in a distinct niche. Weaknesses are minor: it never says "PDB" or "Protein Data Bank" (the names users will most often use), omits file extensions, and phrases the trigger clause in second person ("Use when you want to").

Suggestions

Include the domain's canonical names and extensions as trigger terms: e.g. "...structures for biomolecules from the Protein Data Bank (PDB/RCSB), including .pdb and .cif files".

Rewrite the trigger clause in third person per the rubric's voice guideline: "Use when the user wants to search for or download..." instead of "Use when you want to...".

DimensionReasoningScore

Specificity

The description lists several concrete, distinct actions — "search for or download experimentally-determined 3D structures", "searching by sequence similarity, structure similarity, chemical and other attributes", and "get metadata about biomolecular structure experiments" — which borders on the comprehensive anchor 5. However, the judging guidelines require penalizing second-person voice ("Use when you want to...") by reducing specificity by 1, so it lands at 4; the capability statements themselves ("Supports searching by...") are otherwise third-person and specific.

4 / 5

Completeness

Both "what" and "when" are explicitly answered with concrete trigger phrases: "Use when you want to search for or download experimentally-determined 3D structures for biomolecules (proteins, nucleic acids, bound ligands)" and "Also use to get metadata about biomolecular structure experiments". This matches anchor 5 — clear what (search/download/metadata with enumerated search modes) plus explicit when clauses — not anchor 4, where the "when" would be vague or implicit.

5 / 5

Trigger Term Quality

Good natural keyword coverage: "3D structures", "proteins", "nucleic acids", "bound ligands", "sequence similarity", "structure similarity", "metadata" are phrases users would naturally say. But it omits the most obvious synonyms a user would utter — "PDB", "Protein Data Bank", "RCSB" — and file extensions like ".pdb" or ".cif", matching anchor 4 ("good keyword coverage; a few natural terms missing") rather than the comprehensive anchor 5.

4 / 5

Distinctiveness Conflict Risk

The niche — experimentally-determined biomolecular 3D structures and their metadata — is clearly distinct with domain-specific triggers (sequence/structure similarity, bound ligands), matching anchor 5's "clear niche with distinct triggers; minimal conflict risk". Anchor 4 would apply if it plausibly overlapped a closely related skill's territory, but experimentally-determined structural biology data has no obvious competing-skill overlap here.

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

google-deepmind/science-skills

Path

skills/pdb_database/SKILL.md

Reviewed

Table of Contents

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