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 skills add beita6969/ScienceClaw --skill pubchem-compoundgit clone --depth 1 https://github.com/beita6969/ScienceClawWrote 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/beita6969/scienceclaw/pubchem-compound)<a href="https://agentmods.dev/skills/beita6969/scienceclaw/pubchem-compound"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/pubchem-compound/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/beita6969/scienceclaw/pubchem-compound"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/pubchem-compound.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00082 | $0.01480 |
| Opus 5 | $0.00041 | $0.00740 |
| Sonnet 5 | $0.00016 | $0.00296 |
| Haiku 4.5 | $0.00008 | $0.00148 |
Grade A, and why
pubchem-compound 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 9d 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.
metadata: { "openclaw": { "emoji": "\u2697\ufe0f", "requires": { "bins": ["curl"] } } } How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PubChem Compound Lookup
Query the PubChem PUG REST API to search over 110 million chemical compounds by name, CID, SMILES, InChI, or molecular formula. Retrieve molecular properties, 2D/3D structures, bioactivity data, and perform similarity or substructure searches.
API Base URL
https://pubchem.ncbi.nlm.nih.gov/rest/pug
API Endpoints
Compound Lookup
Retrieve compound data by name, CID, or SMILES:
# By compound name
curl -s "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/aspirin/JSON" | head -60
# By PubChem CID
curl -s "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/cid/2244/JSON" | head -60
# By SMILES string
curl -s "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/smiles/CC(=O)OC1=CC=CC=C1C(=O)O/JSON" | head -60
# By InChI key
curl -s "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/inchikey/BSYNRYMUTXBXSQ-UHFFFAOYSA-N/JSON" | head -60
Property Retrieval
Fetch specific molecular properties (comma-separated list):
# Common drug-likeness properties (Lipinski's Rule of Five)
curl -s "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/name/ibuprofen/property/MolecularWeight,MolecularFormula,XLogP,HBondDonorCount,HBondAcceptorCount,TPSA/JSON"
# Multiple compounds by CID list
curl -s "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/cid/2244,3672,2519/property/MolecularWeight,XLogP,IUPACName/JSON"
Available properties: MolecularFormula, MolecularWeight, CanonicalSMILES, IsomericSMILES, InChI, InChIKey, IUPACName, XLogP, ExactMass, MonoisotopicMass, TPSA, Complexity, HBondDonorCount, HBondAcceptorCount, RotatableBondCount, HeavyAtomCount, AtomStereoCount, BondStereoCount, Volume3D.
Similarity Search
Find structurally similar compounds using 2D fingerprint Tanimoto similarity:
# Find compounds with >=90% similarity to aspirin
curl -s "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/fastsimilarity_2d/smiles/CC(=O)OC1=CC=CC=C1C(=O)O/cids/JSON?Threshold=90"
# Similarity search returning properties
curl -s "https://pubchem.ncbi.nlm.nih.gov/rest/pug/compound/fastsimilarity_2d/cid/2244/property/MolecularWeight,XLogP,CanonicalSMILES/JSON?Threshold=85&MaxRecords=10"
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.
- 9d ago First seen · 125 lines · 82 tokens per session scan A b8911620ef38
pubchem-compound is a skill published in the GitHub repository beita6969/ScienceClaw (898 stars, last pushed 3mo ago), licensed MIT. It adds 82 tokens to every session and 1,480 once invoked, about $0.0004 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 2026-09-03.
Other skills, from other repositories
biopython
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use…
scanpy
Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualization. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use…
structure-prediction
Protein structure prediction from sequence. ESMFold-based, single GPU, no MSA needed. Predicts 3D structures with pLDDT confidence scores for drug discovery targets.
biomcp
Search and retrieve biomedical data - genes, variants, clinical trials, diagnostic tests, articles, drugs, diseases, pathways, proteins, adverse events, pharmacogenomics, and phenotype-disease matching. Use for gene function, variant pathogenicity, trials, diagnostics, drug safety, pathway context, disease workups…
biomcp-research
Do biomedical literature and variant research with the BioMCP CLI, and file what you learn about the tool itself as issues in the biomcp repo.
biological-expert
Expert-level biology, biotechnology, genetics, bioinformatics, and computational biology. Use when the user mentions biology, biotechnology, genetics, bioinformatics, or genomics, or when the task involves Molecular Biology, Genomics & Bioinformatics, Systems Biology, or Data Analysis.