bioservices

bioservices is a skill for Claude Code, Codex from AndyZhuang/Opentest. It costs 73 tokens per session (2,549 once invoked), scanned A, a copy of bioservices, MIT.

A Python interface to many bioinformatics databases and web services, including UniProt, KEGG, ChEMBL, and Reactome. Bioinformatics is the use of software to study biological data such as genes, proteins, and compounds.

In plain words
What is it for?
Use it to retrieve sequences and annotations, search pathways and compounds, convert database identifiers, run sequence comparisons, and query genomic data.
Why use it?
It removes the need to learn and connect to many different database APIs separately, and helps combine results from multiple biological sources.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python scripts/protein_analysis_workflow.py ZAP70_HUMAN [email protected].

Good fit Use it to retrieve sequences and annotations, search pathways and compounds, convert database identifiers, run sequence comparisons, and query genomic data.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/AndyZhuang/Opentest
agentmods
npx agentmods add skills/andyzhuang/opentest/bioservices

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for bioservices

README.md
[![agentmods](https://agentmods.dev/badge/skills/andyzhuang/opentest/bioservices/github.svg)](https://agentmods.dev/skills/andyzhuang/opentest/bioservices)
Your own site
<a href="https://agentmods.dev/skills/andyzhuang/opentest/bioservices"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/bioservices/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.

agentmods 80×15 button for bioservices

Your own site · 80×15
<a href="https://agentmods.dev/skills/andyzhuang/opentest/bioservices"><img src="https://agentmods.dev/badge/skills/andyzhuang/opentest/bioservices.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,549 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 80% copy Near-identical to another mod 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 5.1 $0.00073 $0.02549
Opus 5 $0.00036 $0.01274
Sonnet 5 $0.00015 $0.00510
Haiku 4.5 $0.00007 $0.00255

Measured 8d ago against content hash d267eb1c7634, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

bioservices scanned grade A with 0 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 8d 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

80% identical to bioservices — 71 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/labclaw/literature/bioservices/SKILL.md · 361 lines

How it starts

The opening of the file, as written. The whole thing — 361 lines — stays where its author put it; the contents beside it link to each section on GitHub.

BioServices

Overview

BioServices is a Python package providing programmatic access to approximately 40 bioinformatics web services and databases. Retrieve biological data, perform cross-database queries, map identifiers, analyze sequences, and integrate multiple biological resources in Python workflows. The package handles both REST and SOAP/WSDL protocols transparently.

When to Use This Skill

This skill should be used when:

  • Retrieving protein sequences, annotations, or structures from UniProt, PDB, Pfam
  • Analyzing metabolic pathways and gene functions via KEGG or Reactome
  • Searching compound databases (ChEBI, ChEMBL, PubChem) for chemical information
  • Converting identifiers between different biological databases (KEGG↔UniProt, compound IDs)
  • Running sequence similarity searches (BLAST, MUSCLE alignment)
  • Querying gene ontology terms (QuickGO, GO annotations)
  • Accessing protein-protein interaction data (PSICQUIC, IntactComplex)
  • Mining genomic data (BioMart, ArrayExpress, ENA)
  • Integrating data from multiple bioinformatics resources in a single workflow

Core Capabilities

1. Protein Analysis

Retrieve protein information, sequences, and functional annotations:

from bioservices import UniProt

u = UniProt(verbose=False)

# Search for protein by name
results = u.search("ZAP70_HUMAN", frmt="tab", columns="id,genes,organism")

# Retrieve FASTA sequence
sequence = u.retrieve("P43403", "fasta")

# Map identifiers between databases
kegg_ids = u.mapping(fr="UniProtKB_AC-ID", to="KEGG", query="P43403")

Key methods:

  • search(): Query UniProt with flexible search terms
  • retrieve(): Get protein entries in various formats (FASTA, XML, tab)
  • mapping(): Convert identifiers between databases

Reference: references/services_reference.md for complete UniProt API details.

2. Pathway Discovery and Analysis

Access KEGG pathway information for genes and organisms:

from bioservices import KEGG

k = KEGG()
k.organism = "hsa"  # Set to human

# Search for organisms
k.lookfor_organism("droso")  # Find Drosophila species

# Find pathways by name
k.lookfor_pathway("B cell")  # Returns matching pathway IDs

# Get pathways containing specific genes
pathways = k.get_pathway_by_gene("7535", "hsa")  # ZAP70 gene

# Retrieve and parse pathway data
data = k.get("hsa04660")
parsed = k.parse(data)

# Extract pathway interactions
interactions = k.parse_kgml_pathway("hsa04660")
relations = interactions['relations']  # Protein-protein interactions

# Convert to Simple Interaction Format
sif_data = k.pathway2sif("hsa04660")

Read the full file on GitHub · 361 lines

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. 8d ago First seen · 361 lines · 73 tokens per session scan A d267eb1c7634

Subscribe to this mod's changes

bioservices is a skill published in the GitHub repository AndyZhuang/Opentest (22 stars, last pushed 6mo ago), licensed MIT. It adds 73 tokens to every session and 2,549 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 80% identical to bioservices, differing in 71 lines, and is treated as a copy.

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