Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add zongtingwei/Bioclaw_Skills_Hub --skill foldseekgit clone --depth 1 https://github.com/zongtingwei/Bioclaw_Skills_HubWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/zongtingwei/bioclaw_skills_hub/foldseek)<a href="https://agentmods.dev/skills/zongtingwei/bioclaw_skills_hub/foldseek"><img src="https://agentmods.dev/badge/skills/zongtingwei/bioclaw_skills_hub/foldseek/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/zongtingwei/bioclaw_skills_hub/foldseek"><img src="https://agentmods.dev/badge/skills/zongtingwei/bioclaw_skills_hub/foldseek.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00101 | $0.01485 |
| Opus 5 | $0.00051 | $0.00743 |
| Sonnet 5 | $0.00020 | $0.00297 |
| Haiku 4.5 | $0.00010 | $0.00148 |
Grade A, and why
foldseek scanned grade A with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X POST "https://search.foldseek.com/api/ticket" \ Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
subprocess.run([ How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Foldseek Structure Search
Prerequisites
| Requirement | Minimum | Recommended |
|---|---|---|
| Python | 3.8+ | 3.10 |
| RAM | 8GB | 16GB |
| Disk | 10GB | 50GB (for local databases) |
How to run
Note: Foldseek can run locally or via web server. No GPU required.
Option 1: Web Server (Quick; rate-limited, use sparingly)
# Upload structure to web server
curl -X POST "https://search.foldseek.com/api/ticket" \
-F "[email protected]" \
-F "database[]=afdb50" \
-F "database[]=pdb100"
Option 2: Local installation
# Install Foldseek
conda install -c conda-forge -c bioconda foldseek
# Search PDB
foldseek easy-search query.pdb /path/to/pdb100 results.m8 tmp/
# Search AlphaFold DB
foldseek easy-search query.pdb /path/to/afdb50 results.m8 tmp/
Option 3: Python API
import subprocess
import pandas as pd
def foldseek_search(query_pdb, database, output="results.m8"):
"""Run Foldseek search."""
subprocess.run([
"foldseek", "easy-search",
query_pdb, database, output, "tmp/",
"--format-output", "query,target,pident,alnlen,evalue,bits"
])
return pd.read_csv(output, sep="\t",
names=["query", "target", "pident", "alnlen", "evalue", "bits"])
Key parameters
| Parameter | Default | Description |
|---|---|---|
--min-seq-id |
0.0 | Minimum sequence identity |
-e |
0.001 | E-value threshold |
--alignment-type |
2 | 0=3Di, 1=TM, 2=3Di+AA |
--max-seqs |
300 | Max hits to pass through prefilter; reducing this affects sensitivity |
Databases
| Database | Description | Size |
|---|---|---|
pdb100 |
PDB clustered at 100% | ~200K structures |
afdb50 |
AlphaFold DB at 50% | ~67M structures |
swissprot |
SwissProt structures | ~500K structures |
cath50 |
CATH domains | ~50K domains |
Output format
# results.m8 (tabular)
query target pident alnlen evalue bits
query 1abc_A 85.2 120 1e-45 180.5
query 2def_B 72.1 115 1e-32 145.2
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 196 lines · 101 tokens per session scan A b46ae3860726
foldseek is a skill published in the GitHub repository zongtingwei/Bioclaw_Skills_Hub (26 stars, last pushed 5mo ago), licensed MIT. It adds 101 tokens to every session and 1,485 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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