Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/learningmatter-mit/atomisticskills/drug-db-pubchemnpx skills add learningmatter-mit/AtomisticSkills --skill drug-db-pubchemgit clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/learningmatter-mit/atomisticskills/drug-db-pubchem)<a href="https://agentmods.dev/skills/learningmatter-mit/atomisticskills/drug-db-pubchem"><img src="https://agentmods.dev/badge/skills/learningmatter-mit/atomisticskills/drug-db-pubchem.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00035 | $0.01362 |
| Opus 5 | $0.00017 | $0.00681 |
| Sonnet 5 | $0.00007 | $0.00272 |
| Haiku 4.5 | $0.00003 | $0.00136 |
Grade A, and why
drug-db-pubchem scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **Dependencies**: Standard library only (`urllib`, `json`, `argparse`). How it starts
The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PubChem Database Query
Goal
To programmatically query the PubChem Compound database using the PUG-REST API and retrieve:
- PubChem Compound IDs (CIDs) from names, SMILES, InChI, InChIKey, or molecular formulas,
- computed molecular properties (e.g., molecular weight, XLogP, TPSA, HBD/HBA),
- optional synonyms (names/identifiers),
- optional structure files (SDF), preferring 3D records when available.
This skill is designed for reproducible, rate-limited queries suitable for automation workflows.
Instructions
1. Search by Compound Name
Look up a compound by its common name. Use --name_type complete (default) for exact match or --name_type word for partial matching.
# Env: base-agent
python .agents/skills/drug-db-pubchem/scripts/query_pubchem.py \
--name "aspirin" \
--name_type complete \
--max_results 5 \
--outdir research/pubchem/aspirin \
--output aspirin.json
For partial name matching (can be noisier):
# Env: base-agent
python .agents/skills/drug-db-pubchem/scripts/query_pubchem.py \
--name "atorvastatin" \
--name_type word \
--max_results 10 \
--outdir research/pubchem/atorvastatin \
--output atorvastatin_word.json
2. Search by SMILES
SMILES may contain characters reserved by URL syntax; this script uses HTTP POST to avoid common failures.
# Env: base-agent
python .agents/skills/drug-db-pubchem/scripts/query_pubchem.py \
--smiles "CC(=O)Oc1ccccc1C(=O)O" \
--max_results 5 \
--outdir research/pubchem/aspirin_smiles \
--output aspirin_smiles.json
3. Search by CID
Most unambiguous lookup method.
# Env: base-agent
python .agents/skills/drug-db-pubchem/scripts/query_pubchem.py \
--cid 2244 \
--outdir research/pubchem/CID_2244 \
--output cid_2244.json
4. Search by InChI or InChIKey
InChI uses HTTP POST (like SMILES) to avoid URL syntax issues.
# Env: base-agent
python .agents/skills/drug-db-pubchem/scripts/query_pubchem.py \
--inchikey "BSYNRYMUTXBXSQ-UHFFFAOYSA-N" \
--outdir research/pubchem/aspirin_inchikey \
--output aspirin_inchikey.json
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 155 lines · 35 tokens per session scan A beb059e75f6b
drug-db-pubchem is a skill published in the GitHub repository learningmatter-mit/AtomisticSkills (161 stars, last pushed 3d ago), licensed MIT. It adds 35 tokens to every session and 1,362 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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