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Install
$ agentstack add skill-cheatthegod-biohermes-query-interpro ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ● Network access Used
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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InterPro Protein Domain Database
Query the InterPro REST API for protein domains, families, and functional sites.
When to Use
- User asks about domains in a protein
- User wants to know what family a protein belongs to
- User asks about functional sites or motifs
- User wants domain architecture visualization
How to Execute
import requests
import json
BASE_URL = "https://www.ebi.ac.uk/interpro/api"
# 1. Get protein annotation (domains/families for a UniProt ID)
def get_protein_domains(uniprot_id):
url = f"{BASE_URL}/protein/uniprot/{uniprot_id}"
r = requests.get(url, headers={"Accept": "application/json"})
r.raise_for_status()
return r.json()
# 2. Get InterPro entry details
def get_interpro_entry(interpro_id):
url = f"{BASE_URL}/entry/interpro/{interpro_id}"
r = requests.get(url, headers={"Accept": "application/json"})
r.raise_for_status()
return r.json()
# 3. Search InterPro by text
def search_interpro(query, max_results=10):
url = f"{BASE_URL}/entry/interpro"
params = {"search": query, "page_size": max_results}
r = requests.get(url, params=params, headers={"Accept": "application/json"})
r.raise_for_status()
return r.json()
# 4. Get domain matches for a protein
def get_domain_matches(uniprot_id):
url = f"{BASE_URL}/protein/uniprot/{uniprot_id}/entry/interpro"
r = requests.get(url, headers={"Accept": "application/json"})
r.raise_for_status()
return r.json()
# Example: TP53 domains
domains = get_domain_matches("P04637")
for result in domains.get("results", []):
meta = result.get("metadata", {})
name = meta.get("name", "N/A")
ipr_type = meta.get("type", "N/A")
accession = meta.get("accession", "N/A")
proteins = result.get("proteins", [])
if proteins:
locations = proteins[0].get("entry_protein_locations", [])
for loc in locations:
for frag in loc.get("fragments", []):
start = frag.get("start", "?")
end = frag.get("end", "?")
print(f"{accession} ({ipr_type}): {name} [{start}-{end}]")
Entry Types
domain— Structural/functional domainfamily— Protein familyhomologous_superfamily— Distant homologsrepeat— Repeated motifsite— Active/binding site
Follow-up Suggestions
- "Want me to compare domains across species?"
- "Should I map these domains onto the 3D structure?"
- "Want me to find other proteins with the same domain?"
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: cheatthegod
- Source: cheatthegod/BioHermes
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.