alterlab-pdb — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited alterlab-pdb (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.
scripts/query_pdb.py — RCSB Search + Data + file APIs (stdlib only, JSON to stdout):
python scripts/query_pdb.py search hemoglobin --rows 25 # full-text search (entry IDs)
python scripts/query_pdb.py entry 4HHB # entry metadata
python scripts/query_pdb.py download 4HHB --format cif # download coordinatesThis 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 import search_attributes as attrs
# Find human protein structures (idiomatic form — recommended)
query = attrs.rcsb_entity_source_organism.scientific_name == "Homo sapiens"
results = list(query())
# OR explicit AttributeQuery with a dotted-path STRING (not the Attr object):
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 SeqSimilarityQuery
query = SeqSimilarityQuery(
value="MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVIDGETCLLDILDTAGQEEYSAMRDQYMRTGEGFLCVFAINNTKSFEDIHHYREQIKRVKDSEDVPMVLVGNKCDLPSRTVDTKQAQDLARSYGIPFIETSAKTRQGVDDAFYTLVREIRKHKEKMSKDGKKKKKKSKTKCVIM",
evalue_cutoff=0.1,
identity_cutoff=0.9,
sequence_type="protein"
)
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 search_attributes as attrs
# High-resolution human proteins
query1 = attrs.rcsb_entity_source_organism.scientific_name == "Homo sapiens"
query2 = attrs.rcsb_entry_info.resolution_combined < 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 DataQuery
# Get entry-level data
query = DataQuery(
input_type="entries",
input_ids=["4HHB"],
return_data_list=["struct.title", "exptl.method"],
)
data = query.exec() # synchronous; returns a dict
entry = data["data"]["entries"][0]
print(entry["struct"]["title"])
print(entry["exptl"][0]["method"])Polymer Entity Information:
from rcsbapi.data import DataQuery
# Get protein/nucleic acid information
query = DataQuery(
input_type="polymer_entities",
input_ids=["4HHB_1"],
return_data_list=["entity_poly.pdbx_seq_one_letter_code"],
)
data = query.exec()
entity = data["data"]["polymer_entities"][0]
print(entity["entity_poly"]["pdbx_seq_one_letter_code"])Building Queries (GraphQL under the hood):
from rcsbapi.data import DataQuery
# DataQuery builds the GraphQL query for you from input_type/input_ids/return_data_list;
# there is no separate fetch(query_type="graphql", ...) entry point.
query = DataQuery(
input_type="entries",
input_ids=["4HHB"],
return_data_list=[
"struct.title",
"exptl.method",
"rcsb_entry_info.resolution_combined",
"rcsb_entry_info.deposited_atom_count",
],
)
# Inspect the auto-generated GraphQL / open it in the editor:
print(query.get_editor_link())
data = query.exec()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 DataQuery
# Get experimental details
query = DataQuery(
input_type="entries",
input_ids=["4HHB"],
return_data_list=[
"rcsb_entry_info.resolution_combined",
"exptl.method",
"rcsb_accession_info.deposit_date",
],
)
data = query.exec()["data"]["entries"][0]
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 DataQuery
pdb_ids = ["4HHB", "1MBN", "1GZX"] # Hemoglobin, myoglobin, etc.
# A single DataQuery can fetch all entries at once
query = DataQuery(
input_type="entries",
input_ids=pdb_ids,
return_data_list=[
"rcsb_id",
"struct.title",
"rcsb_entry_info.resolution_combined",
"rcsb_entity_source_organism.scientific_name",
],
)
results = {}
for data in query.exec()["data"]["entries"]:
pdb_id = data["rcsb_id"]
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")
}
# 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 (rcsb-api, current major version 1.x; examples here target >=1.7):
uv pip install "rcsb-api>=1.7"The rcsb-api package provides unified access to both Search and Data APIs through the rcsbapi.search and rcsbapi.data modules. (The older rcsbsearchapi package is superseded by rcsb-api and its import rcsbsearchapi path is gone — prefer rcsb-api for new code.)
The scripts/query_pdb.py helper needs none of this — it hits the public REST APIs with only the Python standard library.
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.