deepchem
No security findings. Scanned 1 time, most recently 2026-10-21.
Second scanner: NVIDIA SkillSpector
Independent static run, no language model, over the same files as the Cisco scan above. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Builds molecular property prediction and MoleculeNet workflows with DeepChem, including SMILES featurization, scaffold or grouped holdouts, masked labels, graph models and explicit pretrained encoder transfer. Used for ADMET, toxicity, solubility and chemistry ML when DeepChem data/model contracts and scientific validation are needed.
- Package
- 10 files, 69 KB
- SKILL.md
- 1023 words, 11 sections
- Code
- Python (4)
- Allowed tools
ReadWriteEditBash- License
- MIT license
- Compatibility
- Requires Python 3.11 for the tested DeepChem 2.8.0 stack. Molecular workflows need RDKit. Torch, Transformers, torch-geometric or DGL/DGL-LifeSci depend on the chosen model. Network is needed only for package, benchmark or model downloads.
SKILL.md covers: DeepChem · When to use · Workflow · Essential model contracts · Installation · Bundled scripts · ESOL log10(mol/L), or custom continuous targets in their declared input units. · Model-specific graph features, including bonds where required. · Explicit HF network + tokenizer; single complete task only. · References and validation · Citing Scientific Agent Skills
Findings
No findings. SAFE
What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 8.8 KB |
references/api_reference.md | doc | 8.3 KB |
references/core_capabilities.md | doc | 3.6 KB |
references/review.md | doc | 5.2 KB |
references/typical_workflows.md | doc | 3.1 KB |
references/workflows.md | doc | 7.0 KB |
scripts/_common.py | script | 6.3 KB |
scripts/graph_neural_network.py | script | 9.3 KB |
scripts/predict_solubility.py | script | 6.8 KB |
scripts/transfer_learning.py | script | 11 KB |
External hosts referenced
github.com huggingface.co deepchem.readthedocs.io arxiv.org pypi.org doi.org export.arxiv.org www.dgl.ai
Hostnames that appear in the skill's files. Referencing a host is not a finding; compare against the findings above and the skill's stated purpose.
Package contents recorded 2026-10-22 at commit 593377bb0487. The scan above ran against the version current at scan time; the two can differ if the skill has since been updated.
What we checked
- Static analyzer. Pattern rules over SKILL.md and bundled files: known-bad commands, exfiltration URLs, secrets, obfuscation.
- Bytecode analyzer.
- Pipeline analyzer.
- Correlation analyzer.
- Behavioral analyzer. Checks what the skill asks the agent to do against what its description claims it does.
- Trigger analyzer. Looks for instructions that fire on conditions the user did not ask for.
What we did not check
- Runtime behaviour. The skill was not executed; findings come from reading its files.
- Anything fetched at install or run time, including remote scripts, package dependencies, and URLs the skill tells the agent to open.
- Content the analyzers cannot read: images, binaries, and some non-English text.
- Known scanner bypass classes. See the methodology and limitations page.
Sources
- Repository: https://github.com/K-Dense-AI/scientific-agent-skills
- Raw scan result: skills-deepchem-scan.json
- Badge for your README:
- Request a re-scan