bio-interaction-databases

A tool for querying protein and gene interaction databases, including STRING, BioGRID, and IntAct. It retrieves interaction partners, confidence scores, and functional-enrichment results through their APIs.

In plain words
What is it for?
Use it to build interaction networks from gene lists, examine protein partners, compare confidence scores, and add biological context to experiments.
Why use it?
It brings known biological relationships into a form that code can analyze instead of requiring manual database searches.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/thesecondfox/skill/bio-database-access-interaction-databases
Any agent
npx skills add thesecondfox/skill --skill bio-database-access-interaction-databases
Clone the repo
git clone --depth 1 https://github.com/thesecondfox/skill

Made for: Claude Code, Codex.

Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,408 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00065 $0.02408
Opus 5 $0.00032 $0.01204
Sonnet 5 $0.00013 $0.00482
Haiku 4.5 $0.00006 $0.00241

Measured 2d ago against content hash e073d811e702, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

bio-interaction-databases scanned grade A with 1 finding 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 2d 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.

- Python: `requests.get()` against STRING/BioGRID REST endpoints + `pandas` for parsing
Common_Skills/bio-database-access-interaction-databases/SKILL.md · 270 lines

How it starts

The opening of the file, as written. The whole thing — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Version Compatibility

Reference examples tested with: BioPython 1.83+, pandas 2.2+

Before using code patterns, verify installed versions match. If versions differ:

  • Python: pip show <package> then help(module.function) to check signatures

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Interaction Databases

Query protein-protein interaction (PPI) and gene interaction databases to build and analyze biological networks.

"Get protein interactions for a gene list" → Query PPI databases (STRING, BioGRID, IntAct) via REST APIs to retrieve interaction partners and confidence scores.

  • Python: requests.get() against STRING/BioGRID REST endpoints + pandas for parsing

STRING API

Query Interactions

import requests
import pandas as pd
from io import StringIO

STRING_API = 'https://version-12-0.string-db.org/api'

def get_string_interactions(genes, species=9606, score_threshold=400):
    '''Fetch PPI from STRING. species: 9606=human, 10090=mouse, 7227=fly'''
    url = f'{STRING_API}/tsv/network'
    params = {
        'identifiers': '%0d'.join(genes),
        'species': species,
        'required_score': score_threshold,
        'caller_identity': 'bioskills'
    }
    response = requests.get(url, params=params)
    return pd.read_csv(StringIO(response.text), sep='\t')

genes = ['TP53', 'BRCA1', 'MDM2', 'ATM', 'CHEK2', 'CDK2']
interactions = get_string_interactions(genes, score_threshold=700)
interactions[['preferredName_A', 'preferredName_B', 'score']].head()

STRING Confidence Score Tiers

Threshold Tier Guidance
150 Low Includes transferred and text-mined; noisy
400 Medium Default. Balanced sensitivity/specificity
700 High Recommended for network analysis. Good confidence
900 Highest Experimentally validated core. Very stringent

Use 700+ for publication-quality networks. Use 400 for exploratory analysis where recall matters.

Read the full file on GitHub · 270 lines

Files

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.

Changes

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.

  1. 2d ago First seen · 270 lines · 65 tokens per session scan A e073d811e702

Subscribe to this mod's changes

bio-interaction-databases is a skill published in the GitHub repository thesecondfox/skill (3 stars, last pushed 5mo ago), licensed MIT. It adds 65 tokens to every session and 2,408 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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