pdb-database — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited pdb-database (Agent Skill) and scored it 45/100 (orange). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 2 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 2 flagged
A base64 string of 128+ characters appears in a documentation file. Encoded prompt injection hides the hostile instruction in base64 — invisible to keyword filters — and relies on the agent's ability to decode it at runtime. There is no normal authoring reason to embed a multi-hundred-byte base64 blob in skill docs.
*.sig, SIGNATURES) outside the documentation.A base64 string of 128+ characters appears in a documentation file. Encoded prompt injection hides the hostile instruction in base64 — invisible to keyword filters — and relies on the agent's ability to decode it at runtime. There is no normal authoring reason to embed a multi-hundred-byte base64 blob in skill docs.
*.sig, SIGNATURES) outside the documentation.Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
RCSB PDB is the worldwide repository for 3D structural data of biological macromolecules. Search for structures, retrieve coordinates and metadata, perform sequence and structure similarity searches across 200,000+ experimentally determined structures and computed models.
This skill should be used when:
Find PDB entries using various search criteria:
Text Search: Search by protein name, keywords, or descriptions
from rcsbapi.search import TextQuery
query = TextQuery("hemoglobin")
results = list(query())
print(f"Found {len(results)} structures")Attribute Search: Query specific properties (organism, resolution, method, etc.)
from rcsbapi.search import AttributeQuery
from rcsbapi.search.attrs import rcsb_entity_source_organism
# Find human protein structures
query = AttributeQuery(
attribute=rcsb_entity_source_organism.scientific_name,
operator="exact_match",
value="Homo sapiens"
)
results = list(query())Sequence Similarity: Find structures similar to a given sequence
from rcsbapi.search import SequenceQuery
query = SequenceQuery(
value="MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVIDGETCLLDILDTAGQEEYSAMRDQYMRTGEGFLCVFAINNTKSFEDIHHYREQIKRVKDSEDVPMVLVGNKCDLPSRTVDTKQAQDLARSYGIPFIETSAKTRQGVDDAFYTLVREIRKHKEKMSKDGKKKKKKSKTKCVIM",
evalue_cutoff=0.1,
identity_cutoff=0.9
)
results = list(query())Structure Similarity: Find structures with similar 3D geometry
from rcsbapi.search import StructSimilarityQuery
query = StructSimilarityQuery(
structure_search_type="entry",
entry_id="4HHB" # Hemoglobin
)
results = list(query())Combining Queries: Use logical operators to build complex searches
from rcsbapi.search import TextQuery, AttributeQuery
from rcsbapi.search.attrs import rcsb_entry_info
# High-resolution human proteins
query1 = AttributeQuery(
attribute=rcsb_entity_source_organism.scientific_name,
operator="exact_match",
value="Homo sapiens"
)
query2 = AttributeQuery(
attribute=rcsb_entry_info.resolution_combined,
operator="less",
value=2.0
)
combined_query = query1 & query2 # AND operation
results = list(combined_query())Access detailed information about specific PDB entries:
Basic Entry Information:
from rcsbapi.data import Schema, fetch
# Get entry-level data
entry_data = fetch("4HHB", schema=Schema.ENTRY)
print(entry_data["struct"]["title"])
print(entry_data["exptl"][0]["method"])Polymer Entity Information:
# Get protein/nucleic acid information
entity_data = fetch("4HHB_1", schema=Schema.POLYMER_ENTITY)
print(entity_data["entity_poly"]["pdbx_seq_one_letter_code"])Using GraphQL for Flexible Queries:
from rcsbapi.data import fetch
# Custom GraphQL query
query = """
{
entry(entry_id: "4HHB") {
struct {
title
}
exptl {
method
}
rcsb_entry_info {
resolution_combined
deposited_atom_count
}
}
}
"""
data = fetch(query_type="graphql", query=query)Retrieve coordinate files in various formats:
Download Methods:
https://files.rcsb.org/download/{PDB_ID}.pdbhttps://files.rcsb.org/download/{PDB_ID}.cifhttps://files.rcsb.org/download/{PDB_ID}.pdb1 (for assembly 1)Example Download:
import requests
pdb_id = "4HHB"
# Download PDB format
pdb_url = f"https://files.rcsb.org/download/{pdb_id}.pdb"
response = requests.get(pdb_url)
with open(f"{pdb_id}.pdb", "w") as f:
f.write(response.text)
# Download mmCIF format
cif_url = f"https://files.rcsb.org/download/{pdb_id}.cif"
response = requests.get(cif_url)
with open(f"{pdb_id}.cif", "w") as f:
f.write(response.text)Common operations with retrieved structures:
Parse and Analyze Coordinates: Use BioPython or other structural biology libraries to work with downloaded files:
from Bio.PDB import PDBParser
parser = PDBParser()
structure = parser.get_structure("protein", "4HHB.pdb")
# Iterate through atoms
for model in structure:
for chain in model:
for residue in chain:
for atom in residue:
print(atom.get_coord())Extract Metadata:
from rcsbapi.data import fetch, Schema
# Get experimental details
data = fetch("4HHB", schema=Schema.ENTRY)
resolution = data.get("rcsb_entry_info", {}).get("resolution_combined")
method = data.get("exptl", [{}])[0].get("method")
deposition_date = data.get("rcsb_accession_info", {}).get("deposit_date")
print(f"Resolution: {resolution} Å")
print(f"Method: {method}")
print(f"Deposited: {deposition_date}")Process multiple structures efficiently:
from rcsbapi.data import fetch, Schema
pdb_ids = ["4HHB", "1MBN", "1GZX"] # Hemoglobin, myoglobin, etc.
results = {}
for pdb_id in pdb_ids:
try:
data = fetch(pdb_id, schema=Schema.ENTRY)
results[pdb_id] = {
"title": data["struct"]["title"],
"resolution": data.get("rcsb_entry_info", {}).get("resolution_combined"),
"organism": data.get("rcsb_entity_source_organism", [{}])[0].get("scientific_name")
}
except Exception as e:
print(f"Error fetching {pdb_id}: {e}")
# Display results
for pdb_id, info in results.items():
print(f"\n{pdb_id}: {info['title']}")
print(f" Resolution: {info['resolution']} Å")
print(f" Organism: {info['organism']}")Install the official RCSB PDB Python API client:
# Current recommended package
pip install rcsb-api
# For legacy code (deprecated, use rcsb-api instead)
pip install rcsbsearchapiThe rcsb-api package provides unified access to both Search and Data APIs through the rcsbapi.search and rcsbapi.data modules.
PDB ID: Unique 4-character identifier (e.g., "4HHB") for each structure entry. AlphaFold and ModelArchive entries start with "AF_" or "MA_" prefixes.
mmCIF/PDBx: Modern file format that uses key-value structure, replacing legacy PDB format for large structures.
Biological Assembly: The functional form of a macromolecule, which may contain multiple copies of chains from the asymmetric unit.
Resolution: Measure of detail in crystallographic structures (lower values = higher detail). Typical range: 1.5-3.5 Å for high-quality structures.
Entity: A unique molecular component in a structure (protein chain, DNA, ligand, etc.).
This skill includes reference documentation in the references/ directory:
Comprehensive API documentation covering:
Use this reference when you need in-depth information about API capabilities, complex query construction, or detailed data schema information.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.