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版本数
在 OpenClaw 中安装
/install pharmaclaw-pharmacology-agent
功能描述
Pharmacology agent for ADME/PK profiling of drug candidates from SMILES. Computes drug-likeness (Lipinski Ro5, Veber rules), QED, SA Score, ADME predictions...
安全使用建议
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).
功能分析
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.
能力评估
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.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install pharmaclaw-pharmacology-agent - 安装完成后，直接呼叫该 Skill 的名称或使用
/pharmaclaw-pharmacology-agent触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v2.0.0
Full release: ADME/PK profiling, Lipinski, QED, BBB, CYP3A4, PAINS alerts
元数据
常见问题
PharmaClaw Pharmacology Agent 是什么？
Pharmacology agent for ADME/PK profiling of drug candidates from SMILES. Computes drug-likeness (Lipinski Ro5, Veber rules), QED, SA Score, ADME predictions... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 366 次。
如何安装 PharmaClaw Pharmacology Agent？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install pharmaclaw-pharmacology-agent」即可一键安装，无需额外配置。
PharmaClaw Pharmacology Agent 是免费的吗？
是的，PharmaClaw Pharmacology Agent 完全免费（开源免费），可自由下载、安装和使用。
PharmaClaw Pharmacology Agent 支持哪些平台？
PharmaClaw Pharmacology Agent 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 PharmaClaw Pharmacology Agent？
由 Cheminem（@cheminem）开发并维护，当前版本 v2.0.0。
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