chembl-database

chembl-database is a skill for Claude Code, Codex from x-cmd/skill. It costs 45 tokens per session (2,632 once invoked), scanned A, a copy of chembl-database, Apache-2.0.

A programming interface to ChEMBL, a curated database of drug-like molecules and their measured effects on biological targets. Bioactivity values such as IC50 and Ki describe how strongly a compound affects a target.

In plain words
What is it for?
Use it to find compounds by name or structure, retrieve target and bioactivity data, identify inhibitors or other active molecules, compare compounds, and support drug-discovery studies.
Why use it?
It lets medicinal-chemistry code search compounds, targets, and activity measurements without manually browsing a large drug-discovery database. Structure searches can also narrow results to similar or matching molecules.

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/x-cmd/skill/chembl-database
Any agent
npx skills add x-cmd/skill --skill chembl-database
Clone the repo
git clone --depth 1 https://github.com/x-cmd/skill

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 chembl-database

README.md
[![agentmods](https://agentmods.dev/badge/skills/x-cmd/skill/chembl-database.svg)](https://agentmods.dev/skills/x-cmd/skill/chembl-database)
Your own site
<a href="https://agentmods.dev/skills/x-cmd/skill/chembl-database"><img src="https://agentmods.dev/badge/skills/x-cmd/skill/chembl-database.svg" alt="Measured on agentmods" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,632 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 86% 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 $0.00045 $0.02632
Opus 5 $0.00023 $0.01316
Sonnet 5 $0.00009 $0.00526
Haiku 4.5 $0.00005 $0.00263

Measured yesterday against content hash 2171fdbfa3e6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

chembl-database 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 yesterday.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/example_queries.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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

86% identical to chembl-database — 6 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.

data/k-dense-ai/chembl-database/SKILL.md · 389 lines

How it starts

The opening of the file, as written. The whole thing — 389 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ChEMBL Database

Overview

ChEMBL is a manually curated database of bioactive molecules maintained by the European Bioinformatics Institute (EBI), containing over 2 million compounds, 19 million bioactivity measurements, 13,000+ drug targets, and data on approved drugs and clinical candidates. Access and query this data programmatically using the ChEMBL Python client for drug discovery and medicinal chemistry research.

When to Use This Skill

This skill should be used when:

  • Compound searches: Finding molecules by name, structure, or properties
  • Target information: Retrieving data about proteins, enzymes, or biological targets
  • Bioactivity data: Querying IC50, Ki, EC50, or other activity measurements
  • Drug information: Looking up approved drugs, mechanisms, or indications
  • Structure searches: Performing similarity or substructure searches
  • Cheminformatics: Analyzing molecular properties and drug-likeness
  • Target-ligand relationships: Exploring compound-target interactions
  • Drug discovery: Identifying inhibitors, agonists, or bioactive molecules

Installation and Setup

Python Client

The ChEMBL Python client is required for programmatic access:

uv pip install chembl_webresource_client

Basic Usage Pattern

from chembl_webresource_client.new_client import new_client

# Access different endpoints
molecule = new_client.molecule
target = new_client.target
activity = new_client.activity
drug = new_client.drug

Core Capabilities

1. Molecule Queries

Retrieve by ChEMBL ID:

molecule = new_client.molecule
aspirin = molecule.get('CHEMBL25')

Search by name:

results = molecule.filter(pref_name__icontains='aspirin')

Filter by properties:

# Find small molecules (MW <= 500) with favorable LogP
results = molecule.filter(
    molecule_properties__mw_freebase__lte=500,
    molecule_properties__alogp__lte=5
)

2. Target Queries

Retrieve target information:

target = new_client.target
egfr = target.get('CHEMBL203')

Read the full file on GitHub · 389 lines

Files

What ships with it

2 files 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. yesterday First seen · 389 lines · 45 tokens per session scan A 2171fdbfa3e6

Subscribe to this mod's changes

chembl-database is a skill published in the GitHub repository x-cmd/skill (26 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 45 tokens to every session and 2,632 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to chembl-database, differing in 6 lines, and is treated as a copy.

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