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Install in OpenClaw
/install pharmaclaw-pharmacology-agent
Description
Pharmacology agent for ADME/PK profiling of drug candidates from SMILES. Computes drug-likeness (Lipinski Ro5, Veber rules), QED, SA Score, ADME predictions...
Usage Guidance
This skill appears to do what it says (RDKit-based ADME and optional ADMETlab API predictions), but pay attention to two things before using it:
- Dependency availability: The package metadata lists no required binaries, but the scripts need Python packages (rdkit and requests) and optional RDKit contrib modules (SA_Score, PAINS). Ensure these are installed in a controlled environment before running.
- Data exposure / IP risk: When ADMETlab 3.0 is reachable, the skill will POST your SMILES to https://admetlab3.scbdd.com. If your molecules are proprietary, confidential, or covered by IP restrictions, do not run this skill without either removing/patching the admetlab call (force local-only RDKit fallback) or confirming the external service's data handling/privacy terms. Consider running the tool offline (use chain_entry.py which can operate purely with RDKit if ADMETlab is unavailable) or auditing admetlab3.py to add an explicit opt-in flag to enable external queries.
Also consider running the code in an isolated environment (container) and reviewing the code locally before supplying sensitive inputs. If you need help patching the script to disable network calls by default, ask and provide the preferred behavior (always-local vs explicit --use-admetlab flag).
Capability Analysis
Type: OpenClaw Skill
Name: pharmaclaw-pharmacology-agent
Version: 2.0.0
The OpenClaw skill bundle is benign. Its purpose is clearly defined as pharmacology profiling using RDKit and the ADMETlab 3.0 API. All code (`scripts/admetlab3.py`, `scripts/chain_entry.py`) and documentation (`SKILL.md`, `references/api_reference.md`) align with this stated purpose. The only external network call is to the legitimate ADMETlab 3.0 service (admetlab3.scbdd.com) for ML-based predictions, which is an explicit and transparent part of the skill's functionality. There is no evidence of data exfiltration, malicious execution, persistence mechanisms, prompt injection attempts against the agent, or obfuscation. A minor version inconsistency between `_meta.json`/`SKILL.md` (v2.0.0) and `scripts/chain_entry.py` (v1.1.0) is a non-security bug.
Capability Assessment
Purpose & Capability
The code and SKILL.md match the stated purpose: RDKit descriptor calculations, rule-based ADME heuristics, optional ADMETlab 3.0 ML integration. However, the skill metadata declares no required binaries or env vars while the code clearly requires Python packages (rdkit, requests) and optional RDKit contrib modules (SA_Score, PAINS catalog). This omission is an inconsistency (missing dependency declarations) but not necessarily malicious.
Instruction Scope
The runtime instructions direct calling scripts/chain_entry.py which in turn may call scripts/admetlab3.py that performs an HTTP POST of the SMILES to ADMETlab 3.0 (https://admetlab3.scbdd.com). Transmitting SMILES to a third-party service can leak proprietary chemical structures/IP. The SKILL.md mentions ADMETlab integration (so the network call is documented) but there is no clear user warning about privacy/IP risk or an explicit opt-out to force local-only RDKit fallback.
Install Mechanism
No install spec is provided (instruction-only), which avoids arbitrary downloads, but the included code depends on heavy third-party libraries (RDKit, requests, optional RDKit contrib modules). Because these are not declared in metadata, users may run into missing-dependency failures or silently run with reduced functionality. There are no suspicious external installers or unusual download URLs in the package itself.
Credentials
The skill does not request credentials or environment variables, which is appropriate. However, it will transmit input SMILES over the network to a third-party API when available; that network access effectively exposes potentially sensitive data (chemical structures). From a credentials perspective this is proportional, but from a data-exposure perspective it is a material privacy/IP concern that should be made explicit to the user.
Persistence & Privilege
The skill does not request always:true, does not modify other skills or system config, and has no elevated persistence or privileges. It runs only when invoked and prints JSON to stdout; no evidence of self-installation or system-wide changes.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install pharmaclaw-pharmacology-agent - After installation, invoke the skill by name or use
/pharmaclaw-pharmacology-agent - Provide required inputs per the skill's parameter spec and get structured output
Version History
v2.0.0
Full release: ADME/PK profiling, Lipinski, QED, BBB, CYP3A4, PAINS alerts
Metadata
Frequently Asked Questions
What is PharmaClaw Pharmacology Agent?
Pharmacology agent for ADME/PK profiling of drug candidates from SMILES. Computes drug-likeness (Lipinski Ro5, Veber rules), QED, SA Score, ADME predictions... It is an AI Agent Skill for Claude Code / OpenClaw, with 366 downloads so far.
How do I install PharmaClaw Pharmacology Agent?
Run "/install pharmaclaw-pharmacology-agent" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is PharmaClaw Pharmacology Agent free?
Yes, PharmaClaw Pharmacology Agent is completely free (open-source). You can download, install and use it at no cost.
Which platforms does PharmaClaw Pharmacology Agent support?
PharmaClaw Pharmacology Agent is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created PharmaClaw Pharmacology Agent?
It is built and maintained by Cheminem (@cheminem); the current version is v2.0.0.
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