### Foldseek Structural Search
Works with
name: "foldseek-structural-search"
description: "Performs 3D structural searches of proteins against various databases (PDB, AlphaFold, CATH, MGnify, etc.) using the Foldseek API. Use ONLY when the user provides a physical 3D coordinate file (.cif, ..."
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionfoldseek-structural-searchExecute the skills CLI command in your project's root directory to begin installation:
Fetches foldseek-structural-search from google-deepmind/science-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate foldseek-structural-search. Access via /foldseek-structural-search in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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| name | foldseek-structural-search |
| description | > Performs 3D structural searches of proteins against various databases (PDB, AlphaFold, CATH, MGnify, etc.) using the Foldseek API. Use ONLY when the user provides a physical 3D coordinate file (.cif, .mmcif, or .pdb) and wants to find structurally similar proteins. Do NOT use if the user only provides a protein sequence, gene name, or UniProt ID. |
uv: Read the uv skill and follow its Setup instructions to ensure
uv is installed and on PATH.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.
.pdb, .cif, or .mmcif file
path..md file for
your immediate summary. The JSON is saved purely for subsequent, specialized
tool use..cif, .mmcif, or .pdb file in their workspace.
afdb50, afdb-swissprot, pdb100, BFVD,
mgnify_esm30, cath50, gmgcl_id, bfmd, afdb-proteome.proteinA_foldseek_results.json and proteinA_foldseek_results.md)..md file:
uv run scripts/search.py <path-to-file> -o <generated-filename.json> > <generated-filename.md>uv run scripts/search.py <path-to-file> -o <generated-filename.json> --databases <db1,db2,db3> > <generated-filename.md>.md file..md file carefully
to view the Markdown table.Target ID column for the reported matches.
.json and .md)
and their locations so they can be seamlessly used in subsequent analysis
steps.and ask them to verify the file path.
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
google-deepmind/science-skills
google-deepmind/science-skills
google-deepmind/science-skills
K-Dense-AI/scientific-agent-skills
K-Dense-AI/scientific-agent-skills
K-Dense-AI/scientific-agent-skills
foldseek-structural-search fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added foldseek-structural-search from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
foldseek-structural-search reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in foldseek-structural-search — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
foldseek-structural-search is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in foldseek-structural-search — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: foldseek-structural-search is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for foldseek-structural-search matched our evaluation — installs cleanly and behaves as described in the markdown.
We added foldseek-structural-search from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: foldseek-structural-search is focused, and the summary matches what you get after install.
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