learningmatter-mit
Registry indexed
chem-hazard-toxicity
Extract explicit safety warnings, GHS classifications, LD50 toxicity profiles, and acute oral toxicity triage from PubChem PUG VIEW.
Registry indexed
Extract explicit safety warnings, GHS classifications, LD50 toxicity profiles, and acute oral toxicity triage from PubChem PUG VIEW.
Extract explicit safety warnings, GHS classifications, LD50 toxicity profiles, and acute oral toxicity triage from PubChem PUG VIEW.
Source documentation, not instructions for this website. Review permissions before running any commands.
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, and performs GHS Acute Toxicity Category assignment and hazard statement consistency analysis.
Provide the precise CID of the molecule to query safety metadata.
# Env: base-agent
python .agents/skills/chem-hazard-toxicity/scripts/get_safety_data.py \
--cid 2519 \
--outdir research/caffeine_safety \
--output safety_caffeine.json
Use --triage to extract consensus GHS statements ($\ge 50%$), lowest rat oral LD50, GHS acute oral category (1–5 or unclassified), and check oral hazard code consistency:
# Env: base-agent
python .agents/skills/chem-hazard-toxicity/scripts/get_safety_data.py \
--cid 2519 \
--triage \
--outdir research/caffeine_safety \
--output triage_caffeine.json
Import helper functions directly into python scripts:
from scripts.get_safety_data import (
extract_consensus_ghs_codes,
extract_lowest_rat_oral_ld50,
assign_acute_oral_category,
check_oral_code_consistency,
profile_compound,
)
profile = profile_compound(2519, threshold_percent=50.0)
# Returns dict with cid, consensus_ghs_codes, oral_rat_ld50_mg_kg, oral_rat_ld50_evidence, acute_oral_category, ghs_oral_code_consistent
GHS Category & Code Consistency Rule:
- Category 1 ($\le 5\text{ mg/kg}$) & Category 2 ($5 < \text{LD}_{50} \le 50\text{ mg/kg}$) $\rightarrow$ expected GHS oral code
H300(Fatal if swallowed).- Category 3 ($50 < \text{LD}_{50} \le 300\text{ mg/kg}$) $\rightarrow$
H301(Toxic if swallowed).- Category 4 ($300 < \text{LD}_{50} \le 2000\text{ mg/kg}$) $\rightarrow$
H302(Harmful if swallowed).- Category 5 ($2000 < \text{LD}_{50} \le 5000\text{ mg/kg}$) $\rightarrow$
H303(May be harmful if swallowed).unclassified($> 5000\text{ mg/kg}$) $\rightarrow$ empty set ({}).
HTTP 503/429 rate limiting via exponential backoff.Author: Bowen Deng Contact: GitHub @learningmatter-mit
name: chem-hazard-toxicity description: Extract explicit safety warnings, GHS classifications, LD50 toxicity profiles, and acute oral toxicity triage from PubChem PUG VIEW. category: [chemistry, drug-discovery]
---
name: chem-hazard-toxicity
description: Extract explicit safety warnings, GHS classifications, LD50 toxicity profiles, and acute oral toxicity triage from PubChem PUG VIEW.
category: [chemistry, drug-discovery]
---
# 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, and performs GHS Acute Toxicity Category assignment and hazard statement consistency analysis.
## Instructions
### 1. Extract Safety Profile by CID
Provide the precise CID of the molecule to query safety metadata.
```bash
# Env: base-agent
python .agents/skills/chem-hazard-toxicity/scripts/get_safety_data.py \
--cid 2519 \
--outdir research/caffeine_safety \
--output safety_caffeine.json
```
### 2. GHS Acute Oral Toxicity Triage Helper
Use `--triage` to extract consensus GHS statements ($\ge 50\%$), lowest rat oral LD50, GHS acute oral category (1–5 or `unclassified`), and check oral hazard code consistency:
```bash
# Env: base-agent
python .agents/skills/chem-hazard-toxicity/scripts/get_safety_data.py \
--cid 2519 \
--triage \
--outdir research/caffeine_safety \
--output triage_caffeine.json
```
### Python API Integration
Import helper functions directly into python scripts:
```python
from scripts.get_safety_data import (
extract_consensus_ghs_codes,
extract_lowest_rat_oral_ld50,
assign_acute_oral_category,
check_oral_code_consistency,
profile_compound,
)
profile = profile_compound(2519, threshold_percent=50.0)
# Returns dict with cid, consensus_ghs_codes, oral_rat_ld50_mg_kg, oral_rat_ld50_evidence, acute_oral_category, ghs_oral_code_consistent
```
> **GHS Category & Code Consistency Rule**:
> - Category 1 ($\le 5\text{ mg/kg}$) & Category 2 ($5 < \text{LD}_{50} \le 50\text{ mg/kg}$) $\rightarrow$ expected GHS oral code `H300` (*Fatal if swallowed*).
> - Category 3 ($50 < \text{LD}_{50} \le 300\text{ mg/kg}$) $\rightarrow$ `H301` (*Toxic if swallowed*).
> - Category 4 ($300 < \text{LD}_{50} \le 2000\text{ mg/kg}$) $\rightarrow$ `H302` (*Harmful if swallowed*).
> - Category 5 ($2000 < \text{LD}_{50} \le 5000\text{ mg/kg}$) $\rightarrow$ `H303` (*May be harmful if swallowed*).
> - `unclassified` ($> 5000\text{ mg/kg}$) $\rightarrow$ empty set (`{}`).
## Constraints
- **Data Availability**: Relies on experimental or reported data listed in PubChem.
- **Network Limits**: Automatically handles standard `HTTP 503/429` rate limiting via exponential backoff.
---
---
**Author:** Bowen Deng
**Contact:** [GitHub @learningmatter-mit](https://github.com/learningmatter-mit)
Skill source recorded
Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.
Review before install: Avoid automatic install
License: MIT
Listed tools are metadata hints, not tested compatibility. Agent prompts are suggested handoffs.
Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.
Version reported in registry metadata; check source releases before relying on it.
Quality
69/100
Promising
Trust
58/100
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
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Audit
75/100
Needs review
Copies are not installs. Installation counts require a reported successful installation; they are not a blanket quality guarantee.