pdb-database

A search and download tool for experimentally measured three-dimensional structures of biomolecules, such as proteins, DNA, RNA, and bound chemicals. It uses the RCSB Protein Data Bank, a public collection of such structures and their experiment details.

In plain words
What is it for?
Use it to find or download biomolecular structures, compare a molecule with known structures, search by chemical or biological attributes, and retrieve details about how a structure was measured.
Why use it?
It helps you find relevant structures without manually searching a large scientific database. Searches can use sequence, shape, chemical properties, and other recorded information.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/google-deepmind/science-skills/pdb_database
Any agent
npx skills add google-deepmind/science-skills --skill pdb_database
Clone the repo
git clone --depth 1 https://github.com/google-deepmind/science-skills

Made for: Claude Code, Codex.

Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,305 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00061 $0.02305
Opus 5 $0.00030 $0.01153
Sonnet 5 $0.00012 $0.00461
Haiku 4.5 $0.00006 $0.00231

Measured yesterday against content hash 9d5f96f75127, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pdb-database scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

The scan reads SKILL.md. This mod also ships 4 executable files (scripts/download_coordinate_files.py, scripts/fetch_pdb_metadata.py, scripts/fetch_schema.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

`curl`, `urllib`, raw HTTP requests, or any other method to access PDB APIs.
skills/pdb_database/SKILL.md · 170 lines

How it starts

The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.

RCSB Protein Data Bank skill

Prerequisites

  1. uv: Read the uv skill and follow its Setup instructions to ensure uv is installed and on PATH.
  2. User Notification: If .licenses/pdb_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://www.rcsb.org/pages/usage-policy, then (2) create the file recording the notification text and timestamp.

Core Rules

  • Always prefer to use the provided scripts. Only as a last resort use curl, urllib, raw HTTP requests, or any other method to access PDB APIs. The scripts automatically enforce required rate limits.
  • Always redirect output to a file. Parse output with e.g. jq, grep, or a short Python snippet. Do NOT print large API responses to stdout to avoid truncation.
  • Notification: If this skill is used, ensure this is mentioned in the output.
  • Explain your queries On completing a task that used PDB JSON/GraphQL queries, explain in clear language what your query did so the user can correct any bad assumptions.

Attribute-based search workflow

  1. Fetch the relevant schema to discover searchable attribute names. For structure attributes: uv run scripts/fetch_schema.py --api search_structure --output schema_structure.txt For chemical attributes: uv run scripts/fetch_schema.py --api search_chemical --output schema_chemical.txt

  2. Grep the schema to find relevant attributes. Grep one keyword at a time and examine many lines — there are lots of similar attributes and you must choose the best match for the user's intent.

  3. Compose and run a JSON search query using the discovered attributes: uv run scripts/search_pdb.py --query '<JSON>' --return_type <RETURN_TYPE> --output results.json Pass the --count_only flag to get just the number of matching entries.

For step 2: some basic PDB concepts (helpful for attribute choice)

Read the full file on GitHub · 170 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 170 lines · 61 tokens per session scan A 9d5f96f75127

Subscribe to this mod's changes

pdb-database is a skill published in the GitHub repository google-deepmind/science-skills (2,794 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 61 tokens to every session and 2,305 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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