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chem-hazard-toxicity

Research
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Extract explicit safety warnings, GHS classifications, and LD50 profiles from PubChem PUG VIEW.

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How to use this skill

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  3. Review the proposed files and risks before you approve installation.
Prompt to paste
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Source SKILL.md: https://github.com/learningmatter-mit/AtomisticSkills/blob/HEAD/.agents/skills/chem-hazard-toxicity/SKILL.md

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First, summarize what it does, its dependencies, license status if identifiable, and any risks. Show the exact files you propose to add under .agents/skills/chem-hazard-toxicity/. Do not write files or run scripts until I approve.

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Copying this prompt does not install or run the skill. Review third-party files before use. Codex skill guide

Chemical Hazard and Toxicity Profiling

Goal

To programmatically extract critical safety information from the PubChem PUG-VIEW API. This skill pulls GHS Classifications, Hazard Classes, and Toxicological properties (like LD50/LC50 experimental animal records) for a given compound based on its CID.

Instructions

1. Extract Safety Profile by CID

Provide the precise CID of the molecule targeting the specific record to query safety metadata. The output is a JSON array of natural language texts sourced from chemical vendors, safety data sheets, and literature.

# Env: base-agent
python .agents/skills/chem-hazard-toxicity/scripts/get_safety_data.py \
  --cid 2519 \
  --outdir research/caffeine_safety \
  --output safety_caffeine.json

Examples

We can test the extraction for Caffeine (CID: 2519), a well documented compound.

# Env: base-agent
python .agents/skills/chem-hazard-toxicity/scripts/get_safety_data.py \
  --cid 2519 \
  --outdir .agents/skills/chem-hazard-toxicity/examples/caffeine \
  --output safety_caffeine.json

Constraints

  • Data Availability: This relies exclusively on experimental or reported data listed in PubChem. Some newly generated molecules or obscure reagents may have empty safety profiles.
  • Network Limits: PubChem PUG VIEW can be rate-limited under heavy load. The script automatically handles standard HTTP 503 blocking via exponential backoff.


Author: Bowen Deng Contact: GitHub @learningmatter-mit