Agent skill

Chembl Database

by aipoch in aipoch/medical-research-skills

Query the ChEMBL database for bioactive molecules, targets, bioactivities, and approved drugs; use this when you need to filter by physicochemical properties (e.g., MW, LogP), chemical structure…

MITAuto-check passedResearch & Science

Install Chembl Database

skills CLI

$ npx skills add aipoch/medical-research-skills --skill chembl-database -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install aipoch/medical-research-skills chembl-database --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'scientific-skills/Evidence Insight/chembl-database' .claude/skills/chembl-database && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "chembl-database" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Evidence%20Insight/chembl-database into .claude/skills/chembl-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chembl-database", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Evidence%20Insight/chembl-database

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add aipoch/medical-research-skills --skill chembl-database -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install aipoch/medical-research-skills chembl-database --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/'scientific-skills/Evidence Insight/chembl-database' .agents/skills/chembl-database && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "chembl-database" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Evidence%20Insight/chembl-database into .agents/skills/chembl-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chembl-database", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add aipoch/medical-research-skills --skill chembl-database -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install aipoch/medical-research-skills chembl-database --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/'scientific-skills/Evidence Insight/chembl-database' .cursor/skills/chembl-database && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "chembl-database" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Evidence%20Insight/chembl-database into .cursor/skills/chembl-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chembl-database", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/aipoch/medical-research-skills.git --path 'scientific-skills/Evidence Insight/chembl-database'

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add aipoch/medical-research-skills --skill chembl-database -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install aipoch/medical-research-skills chembl-database --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/'scientific-skills/Evidence Insight/chembl-database' .gemini/skills/chembl-database && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "chembl-database" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Evidence%20Insight/chembl-database into .gemini/skills/chembl-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chembl-database", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install aipoch/medical-research-skills chembl-database

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add aipoch/medical-research-skills --skill chembl-database -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/'scientific-skills/Evidence Insight/chembl-database' .github/skills/chembl-database && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "chembl-database" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Evidence%20Insight/chembl-database into .github/skills/chembl-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chembl-database", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add aipoch/medical-research-skills --skill chembl-database -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install aipoch/medical-research-skills chembl-database --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/'scientific-skills/Evidence Insight/chembl-database' .opencode/skills/chembl-database && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "chembl-database" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/scientific-skills/Evidence%20Insight/chembl-database into .opencode/skills/chembl-database/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chembl-database", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: chembl-database
GitHub stars: 2k
Token cost: ~1.3k tokens
SKILL.md length: 314 words
Files: 4 (incl. scripts, references)
Skills in repo: 567
Repo updated: Sep 17, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Query the ChEMBL database for bioactive molecules, targets, bioactivities, and approved drugs; use this when you need to filter by physicochemical properties (e.g., MW, LogP), chemical structure…

Tasks that involve Drug discovery and cheminformatics
SKILL.md covers When to Use, Key Features, Dependencies and Example Usage, plus 1 more section
Runs Python scripts from its folder; calls uv

What it does

Chembl Database is an agent skill from aipoch/medical-research-skills. Query the ChEMBL database for bioactive molecules, targets, bioactivities, and approved drugs; use this when you need to filter by physicochemical properties (e.g., MW, LogP), chemical structure (SMILES), or retrieve drug mechanism information.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `chembl-database_audit_result_v1.json`, `references/api_reference.md` and `scripts/query_chembl.py`).

It sits in Research & Science, covering Drug discovery and cheminformatics. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.

When your agent uses it

Tasks that involve Drug discovery and cheminformatics

Example prompts

“/chembl-database”

Requirements

Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- uv
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Chembl Database loads about 1.3k tokens when it runs, and up to ~1.5k if it reads all its reference files. Until then it costs about 65 tokens; SKILL.md has 314 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~65
When it runs · the whole SKILL.md, loaded when a task matches: ~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~1.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 314 words, ~1,303 tokens.

Download SKILL.mdSave it as .claude/skills/chembl-database/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.

name: chembl-database
description: Query the ChEMBL database for bioactive molecules, targets, bioactivities, and approved drugs; use this when you need to filter by physicochemical properties (e.g., MW, LogP), chemical structure (SMILES), or retrieve drug mechanism information.
license: MIT
author: AIPOCH

Source: https://github.com/aipoch/medical-research-skills

When to Use

Find candidate compounds by name or synonym (e.g., searching for “aspirin”) and retrieve their ChEMBL records.
Filter molecules by physicochemical properties (e.g., molecular weight, LogP) to narrow down drug-like candidates.
Look up targets (proteins/complexes) and connect them to ligands and known bioactivity measurements.
Retrieve bioactivity data (e.g., IC50, Ki, EC50) for specific compound–target interactions to support SAR or benchmarking.
Identify approved drugs and fetch mechanism-of-action information for target validation or competitive landscape analysis.

Key Features

Molecule search by preferred name and other metadata fields.
Property-based filtering (e.g., MW, LogP) using ChEMBL API filter syntax.
Structure-aware querying via SMILES (where supported by the API/client).
Target lookup and navigation between targets, molecules, and activities.
Bioactivity retrieval for common endpoints (IC50, Ki, EC50) and related assay context.
Access to drug-related records, including mechanism information for approved drugs.

Dependencies

Python 3.9+ (recommended)
chembl_webresource_client (latest available via pip/uv)

Install:

bash

uv pip install chembl_webresource_client

Additional references (optional, if present in this repository):

references/api_reference.md (filter syntax and resource list)
scripts/query_chembl.py (CLI wrapper example)

Example Usage

python

from chembl_webresource_client.new_client import new_client

def main():
    molecule = new_client.molecule
    target = new_client.target
    activity = new_client.activity
    mechanism = new_client.mechanism

    # 1) Search for molecules by name (case-insensitive substring match)
    mols = list(molecule.filter(pref_name__icontains="aspirin")[:5])
    if not mols:
        raise SystemExit("No molecules found for query.")

    first = mols[0]
    chembl_id = first.get("molecule_chembl_id")
    print("Top molecule hit:", chembl_id, "-", first.get("pref_name"))

    # 2) Filter molecules by a simple property constraint (example: MW <= 500)
    # Note: exact field names and operators depend on ChEMBL API schema.
    druglike = list(molecule.filter(molecule_properties__mw_freebase__lte=500)[:5])
    print("Example drug-like hits (MW<=500):", [m.get("molecule_chembl_id") for m in druglike])

    # 3) Get target information (example: targets containing "COX")
    targets = list(target.filter(pref_name__icontains="cyclooxygenase")[:5])
    print("Example targets:", [(t.get("target_chembl_id"), t.get("pref_name")) for t in targets])

    # 4) Query bioactivity for a molecule (IC50/Ki/EC50 etc. depend on available records)
    # Here we fetch a few activity records linked to the molecule.
    acts = list(activity.filter(molecule_chembl_id=chembl_id)[:5])
    for a in acts:
        print(
            "Activity:",
            a.get("activity_id"),
            "type=", a.get("standard_type"),
            "value=", a.get("standard_value"),
            "units=", a.get("standard_units"),
            "target=", a.get("target_chembl_id"),
        )

    # 5) Retrieve mechanism-of-action records (often used for approved drugs)
    mechs = list(mechanism.filter(molecule_chembl_id=chembl_id)[:5])
    for m in mechs:
        print(
            "Mechanism:",
            "target=", m.get("target_chembl_id"),
            "action=", m.get("action_type"),
            "mechanism=", m.get("mechanism_of_action"),
        )

if __name__ == "__main__":
    main()

Implementation Details

Client/Resources: Uses chembl_webresource_client.new_client.new_client to access resource endpoints such as molecule, target, activity, and mechanism.
Filtering Model: Queries are built via .filter(...) with field lookups and operators (e.g., __icontains, __lte). The exact available fields and supported operators are defined by the ChEMBL API schema; consult references/api_reference.md for the authoritative list and examples.
Pagination/Slicing: Results are iterable and can be sliced (e.g., [:5]) to limit network calls and output size.
Bioactivity Fields: Common normalized fields include standard_type, standard_value, and standard_units. Not all records contain all fields; code should handle missing keys.
Mechanism Retrieval: Mechanism-of-action data is accessed via the mechanism resource and is typically most complete for approved/annotated drugs.
Structure Queries (SMILES): Structure-based search support depends on the API endpoint and client capabilities; when enabled, it is typically performed by passing a SMILES string to the appropriate structure/compound endpoint or filter as documented in references/api_reference.md.

Files

SKILL.md and 3 other files (scripts, references) in scientific-skills/Evidence Insight/chembl-database of aipoch/medical-research-skills.

SKILL.md
chembl-database_audit_result_v1.json
references/api_reference.md
scripts/query_chembl.py

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Chembl Database next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Chembl Database compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Chembl Database this skillaipoch/medical-research-skills	2k	—	~1.3k	Automated safety check: Pass	MIT	21 days ago
MolecodeAtomFlow-AI/MoleCode	305	—	~1.9k	Automated safety check: Pass	MIT	4 mo ago
Drug DiscoveryTommy-yw/RunbookHermes	546	1 repos	~2.3k	Automated safety check: Pass	MIT	4 mo ago
DiffDock Molecular DockingK-Dense-AI/scientific-agent-skills	48k	1 repos	~3k	Automated safety check: Notes	MIT	2 days ago
Biomedical Analysis Dispatchxjtulyc/MedgeClaw	617	1 repos	~2k	Automated safety check: Pass	None	6 mo ago
Edu Chem Reactionwy51ai/edulab	1.4k	—	~1.2k	Automated safety check: Pass	Apache-2.0	9 days ago

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Questions about Chembl Database

What does Chembl Database do?

Query the ChEMBL database for bioactive molecules, targets, bioactivities, and approved drugs; use this when you need to filter by physicochemical properties (e.g., MW, LogP), chemical structure…. Chembl Database is an agent skill from aipoch/medical-research-skills., MW, LogP), chemical structure (SMILES), or retrieve drug mechanism information.

When should I use Chembl Database?

Chembl Database fits situations like: tasks that involve Drug discovery and cheminformatics.

How do I install Chembl Database in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill chembl-database -a claude-code`. Or copy the skill folder (scientific-skills/Evidence Insight/chembl-database in aipoch/medical-research-skills) into .claude/skills/chembl-database in your project. Claude Code loads it when a task matches its description.

How do I install Chembl Database in Codex?

Run `npx skills add aipoch/medical-research-skills --skill chembl-database -a codex`. Or copy the skill folder (scientific-skills/Evidence Insight/chembl-database in aipoch/medical-research-skills) into .agents/skills/chembl-database in your project. Codex loads it when a task matches its description.

Can I use Chembl Database in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/medical-research-skills --skill chembl-database -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/chembl-database, .gemini/skills/chembl-database, .github/skills/chembl-database and .opencode/skills/chembl-database in your project.

What does Chembl Database need to run?

Going by SKILL.md and its folder, Chembl Database needs Python for the scripts in its folder and the command-line tools its instructions call (uv). Our summary lists: Python 3.

Does Chembl Database access the network?

SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Chembl Database safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Chembl Database use?

Chembl Database is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Chembl Database use?

About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 198 tokens, read only when the agent opens those files.

What are the alternatives to Chembl Database?

Skills that share tags, products or a category with Chembl Database: Molecode (AtomFlow-AI/MoleCode, 305 stars), Drug Discovery (Tommy-yw/RunbookHermes, 546 stars), DiffDock Molecular Docking (K-Dense-AI/scientific-agent-skills, 48k stars) and Biomedical Analysis Dispatch (xjtulyc/MedgeClaw, 617 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Chembl Database?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,974 GitHub stars. The repository holds 567 skills in this directory. The repository was last updated on September 17, 2026.

Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Chembl Database

Install Chembl Database

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

When to Use

Key Features

Dependencies

Example Usage

Implementation Details

Files

Compare with similar skills

Similar skills

Molecode

Drug Discovery

DiffDock Molecular Docking

Biomedical Analysis Dispatch

Edu Chem Reaction

Biopipelines

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Questions about Chembl Database

Install Chembl Database

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

When to Use

Key Features

Dependencies

Example Usage

Implementation Details

Files

Compare with similar skills

Similar skills

More from aipoch/medical-research-skills

Related

Questions about Chembl Database