Now liveThe Skillselion MCP - thousands of ranked skills, loaded into your agent mid-task. No install.Get it →
google-deepmind avatar

Foldseek Structural Search

  • 1.1k installs
  • 2.6k repo stars
  • Updated July 7, 2026
  • google-deepmind/science-skills

Foldseek Structural Search is a Claude Code skill that runs fast structural searches of protein structures against Foldseek databases for developers who need similarity lookup from PDB or mmCIF files inside agent workflo

About

Foldseek Structural Search is a google-deepmind/science-skills script skill that runs Foldseek search for a PDB or mmCIF file against structural databases directly from an agent workflow. The bundled script requires Python >=3.10 and executes Foldseek similarity queries as part of computational biology pipelines. Developers reach for Foldseek Structural Search when protein structure files need fast database scanning without manually chaining shell commands and parsing outputs. The skill targets structural bioinformatics engineers embedding Foldseek into automated research and annotation flows.

  • Runs Foldseek searches for PDB/mmCIF files against 9 public databases including AFDB50, PDB100, and CATH50.
  • Respects strict 0.1 queries-per-second rate limit using a shared HTTP client.
  • Constructs manual multipart/form-data payloads for reliable API submission.
  • Returns alignment hits with configurable maximum of 300 results and default E-value of 1000.
  • Designed as a reusable CLI and agent skill for structural biology tasks.

Foldseek Structural Search by the numbers

  • 1,130 all-time installs (skills.sh)
  • +53 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #274 of 2,064 Data Science & ML skills by installs in the Skillselion catalog
  • Security screen: MEDIUM risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/google-deepmind/science-skills --skill foldseek-structural-search

Add your badge

Show developers this skill is listed on Skillselion. Paste this into your README.

Listed on Skillselion
Installs1.1k
repo stars2.6k
Security audit2 / 3 scanners passed
Last updatedJuly 7, 2026
Repositorygoogle-deepmind/science-skills

How do you search protein structures with Foldseek?

Run fast structural searches of protein structures against Foldseek databases directly from their agent workflow.

Who is it for?

Structural bioinformatics developers who need agent-driven Foldseek searches against protein structure databases from PDB or mmCIF inputs.

Skip if: Developers working on sequence-only genomics pipelines without structural PDB or mmCIF files.

When should I use this skill?

A developer provides a PDB or mmCIF structure and asks for Foldseek similarity search against structural databases.

What you get

Foldseek search results, structural similarity hits, and parsed output from PDB/mmCIF queries.

  • Foldseek search results
  • structural similarity hit lists

By the numbers

  • Bundled script requires Python >=3.10

Files

SKILL.mdMarkdownGitHub ↗

Prerequisites

1. `uv`: Read the uv skill and follow its Setup instructions to ensure uv is installed and on PATH. 2. User Notification: If LICENSE_NOTIFICATION.txt does not already exist in this skill directory then (1) prominently notify the user to check the terms at https://search.foldseek.com/search and https://github.com/steineggerlab/foldseek, then (2) create the file recording the notification text and timestamp.

Goal

Submit a user-provided 3D protein structure file (.cif, .mmcif, or .pdb) to the Foldseek web server API to find structurally similar proteins. Report the top structural hits, interpret key alignment metrics, summarize the inferred protein functions, save the Markdown-formatted table to a .md file, and save the full detailed results to a local JSON file.

Core Rules

  • File Requirement: This tool absolutely cannot search by sequence, name,

or accession ID. It strictly requires a .pdb, .cif, or .mmcif file path.

  • Strict Validation: Never bypass the input validation or the database

allowlist check.

  • Do Not Parse the JSON: Rely entirely on the generated .md file for

your immediate summary. The JSON is saved purely for subsequent, specialized tool use.

  • No Raw Parsing: Do not attempt to parse or read the raw 3D coordinates

yourself; always pass the file to the script.

  • Notification: If this skill is used, ensure this is mentioned in the

output.

Instructions

1. Strict Input Validation: Verify that the user has explicitly provided a valid path to a .cif, .mmcif, or .pdb file in their workspace.

  • If the user provided a protein name, an amino acid sequence, or an

accession ID (e.g., a UniProt ID) but NO downloaded structure file, halt immediately. Do not run the script.

  • Inform the user that Foldseek requires a physical 3D coordinate file,

and suggest downloading the structure first (e.g., using the AlphaFold fetch tool). 2. Database Validation: Check if the user requested specific databases to search.

  • Allowed List: afdb50, afdb-swissprot, pdb100, BFVD,

mgnify_esm30, cath50, gmgcl_id, bfmd, afdb-proteome.

  • If the user requests a database NOT on this list, halt immediately.

Do not run the script. Inform the user that the database is unsupported and provide them with the allowed list. 3. Generate File Names: Generate descriptive output file names for both the JSON data and the Markdown table based on the input file (e.g., proteinA_foldseek_results.json and proteinA_foldseek_results.md). 4. Execute the python script based on the user's request, redirecting the standard output into your generated .md file:

  • Default (No databases specified): `uv run scripts/search.py

<path-to-file> -o <generated-filename.json> > <generated-filename.md>`

  • Custom (Valid databases specified): `uv run scripts/search.py

<path-to-file> -o <generated-filename.json> --databases <db1,db2,db3> > <generated-filename.md> 5. The script will query the databases, save the full JSON payload, and write a Markdown-formatted table to your specified .md file. 6. **Read the Results:** Open and read the newly generated .md` file carefully to view the Markdown table. 7. Interpret the Metrics: Summarize the top 3 to 5 structural matches that have meaningfull annotations for the user. When reporting, assess the match quality using these specific fields:

  • Prob (Probability): Values approaching 1.0 (100%) indicate extreme

confidence that the fold is a true structural homologue.

  • Q-Cov (Query Coverage): High percentages mean the match covers the

majority of the query protein's overall shape, rather than just a small local motif.

  • E-value & Seq Identity: Use these to provide additional evolutionary

context. 8. Perform Functional Analysis: Analyze the text descriptions embedded within the Target ID column for the reported matches.

  • Explicitly report the specific protein names/functions of the top

structural homologues.

  • Provide a synthesized overview summarizing the entire variety of

different functions, domains, or protein families found across the whole list of homologues (e.g., "Most hits are portal proteins, but there is also a distinct cluster of viral capsid matches..."). 9. Explicitly inform the user of both newly created files (.json and .md) and their locations so they can be seamlessly used in subsequent analysis steps.

* If the API returns an error or the file is missing, inform the user clearly

and ask them to verify the file path.

Related skills

FAQ

What file formats does Foldseek Structural Search accept?

Foldseek Structural Search accepts PDB and mmCIF protein structure files as input and runs Foldseek search against configured structural databases from an agent-driven workflow.

What Python version does Foldseek Structural Search require?

Foldseek Structural Search requires Python >=3.10 for its bundled script that executes Foldseek structural similarity searches against protein structure databases.

Is Foldseek Structural Search safe to install?

skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

Data Science & MLresearchautomation

This week in AI coding

Five minutes, every Monday - the tools, releases and tactics for developers.

unsubscribe anytime.