interpro-database

interpro-database is a skill for Claude Code, Codex from LeonChaoX/qinyan-academic-skills. It costs 62 tokens per session (2,742 once invoked), scanned A, original, MIT.

A protein database that groups sequences into families, domains, repeats, and functional sites. A domain is a distinct part of a protein that often performs a particular structural or biological job.

In plain words
What is it for?
Use it to predict protein function, map domain structure, classify evolutionary relationships, and retrieve Gene Ontology annotations.
Why use it?
It helps infer what an unfamiliar protein may do by comparing its sequence with known protein regions and families.

Skill for Claude CodeCodex

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

Good fit Use it to predict protein function, map domain structure, classify evolutionary relationships, and retrieve Gene Ontology annotations.

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Install with agentmods
npx agentmods add skills/leonchaox/qinyan-academic-skills/interpro-database
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.

Any agent
npx skills add LeonChaoX/qinyan-academic-skills --skill interpro-database
Clone the repo
git clone --depth 1 https://github.com/LeonChaoX/qinyan-academic-skills

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 interpro-database

README.md
[![agentmods](https://agentmods.dev/badge/skills/leonchaox/qinyan-academic-skills/interpro-database/github.svg)](https://agentmods.dev/skills/leonchaox/qinyan-academic-skills/interpro-database)
Your own site
<a href="https://agentmods.dev/skills/leonchaox/qinyan-academic-skills/interpro-database"><img src="https://agentmods.dev/badge/skills/leonchaox/qinyan-academic-skills/interpro-database/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 interpro-database

Your own site · 80×15
<a href="https://agentmods.dev/skills/leonchaox/qinyan-academic-skills/interpro-database"><img src="https://agentmods.dev/badge/skills/leonchaox/qinyan-academic-skills/interpro-database.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,742 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00062 $0.02742
Opus 5 $0.00031 $0.01371
Sonnet 5 $0.00012 $0.00548
Haiku 4.5 $0.00006 $0.00274

Measured 5d ago against content hash d2e59e100ed0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

interpro-database 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 5d 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.

response = requests.get(url, params=params, headers=headers)
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/08-蛋白质工程与结构生物学/interpro-database/SKILL.md · 306 lines

How it starts

The opening of the file, as written. The whole thing — 306 lines — stays where its author put it; the contents beside it link to each section on GitHub.

InterPro Database

Overview

InterPro (https://www.ebi.ac.uk/interpro/) is a comprehensive resource for protein family and domain classification maintained by EMBL-EBI. It integrates signatures from 13 member databases including Pfam, PANTHER, PRINTS, ProSite, SMART, TIGRFAM, SUPERFAMILY, CDD, and others, providing a unified view of protein functional annotations for over 100 million protein sequences.

InterPro classifies proteins into:

  • Families: Groups of proteins sharing common ancestry and function
  • Domains: Independently folding structural/functional units
  • Homologous superfamilies: Structurally similar protein regions
  • Repeats: Short tandem sequences
  • Sites: Functional sites (active, binding, PTM)

Key resources:

When to Use This Skill

Use InterPro when:

  • Protein function prediction: What function(s) does an uncharacterized protein likely have?
  • Domain architecture: What domains make up a protein, and in what order?
  • Protein family classification: Which family/superfamily does a protein belong to?
  • GO term annotation: Map protein sequences to Gene Ontology terms via InterPro
  • Evolutionary analysis: Are two proteins in the same homologous superfamily?
  • Structure prediction context: What domains should a new protein structure be compared against?
  • Pipeline annotation: Batch-annotate proteomes or novel sequences

Core Capabilities

1. InterPro REST API

Base URL: https://www.ebi.ac.uk/interpro/api/

import requests

BASE_URL = "https://www.ebi.ac.uk/interpro/api"

def interpro_get(endpoint, params=None):
    url = f"{BASE_URL}/{endpoint}"
    headers = {"Accept": "application/json"}
    response = requests.get(url, params=params, headers=headers)
    response.raise_for_status()
    return response.json()

Read the full file on GitHub · 306 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. 5d ago First seen · 306 lines · 62 tokens per session scan A d2e59e100ed0

Subscribe to this mod's changes

interpro-database is a skill published in the GitHub repository LeonChaoX/qinyan-academic-skills (876 stars, last pushed 1mo ago), licensed MIT. It adds 62 tokens to every session and 2,742 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 2026-09-03.

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