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.
69
83%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
View guide
Passed
No findings from the security scan
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.
0b42509
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.