chembl-database

chembl-database is a skill for Claude Code, Codex from silverstein/claude-scientific-skills-desktop. It costs 46 tokens per session (2,459 once invoked), scanned A, a copy of chembl-database, MIT.

A programming interface to ChEMBL, a curated database of biologically active molecules, drug targets, medicines, and laboratory activity measurements.

In plain words
What is it for?
Use it to search compounds by name, structure, or properties; inspect target and drug data; study compound-target relationships; and identify inhibitors or other active molecules.
Why use it?
It avoids searching separate sources for compounds, targets, drug information, and measurements such as IC50 or Ki. Structure searches help find related molecules.

Skill for Claude CodeCodex

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

Good fit Use it to search compounds by name, structure, or properties; inspect target and drug data; study compound-target relationships; and identify inhibitors or other active molecules.

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Install with agentmods
npx agentmods add skills/silverstein/claude-scientific-skills-desktop/chembl-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 silverstein/claude-scientific-skills-desktop --skill chembl-database
Clone the repo
git clone --depth 1 https://github.com/silverstein/claude-scientific-skills-desktop

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/silverstein/claude-scientific-skills-desktop/chembl-database/github.svg)](https://agentmods.dev/skills/silverstein/claude-scientific-skills-desktop/chembl-database)
Your own site
<a href="https://agentmods.dev/skills/silverstein/claude-scientific-skills-desktop/chembl-database"><img src="https://agentmods.dev/badge/skills/silverstein/claude-scientific-skills-desktop/chembl-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 chembl-database

Your own site · 80×15
<a href="https://agentmods.dev/skills/silverstein/claude-scientific-skills-desktop/chembl-database"><img src="https://agentmods.dev/badge/skills/silverstein/claude-scientific-skills-desktop/chembl-database.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,459 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 95% 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 $0.00046 $0.02459
Opus 5 $0.00023 $0.01229
Sonnet 5 $0.00009 $0.00492
Haiku 4.5 $0.00005 $0.00246

Measured 12d ago against content hash 09aa03797fdb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, 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 12d ago.

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

95% identical to chembl-database — 7 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.

corpus/chembl-database/SKILL.md · 384 lines

How it starts

The opening of the file, as written. The whole thing — 384 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 · 384 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. 12d ago First seen · 384 lines · 46 tokens per session scan A 09aa03797fdb

Subscribe to this mod's changes

chembl-database is a skill published in the GitHub repository silverstein/claude-scientific-skills-desktop (22 stars, last pushed 5mo ago), licensed MIT. It adds 46 tokens to every session and 2,459 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to chembl-database, differing in 7 lines, and is treated as a copy.

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