Borrowing it
Nothing to install: this file belongs to omar-A-hassan/medsci-agent. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/omar-A-hassan/medsci-agent/main/.opencode/skills/deepchem/SKILL.mdgit clone --depth 1 https://github.com/omar-A-hassan/medsci-agentWrote 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/omar-a-hassan/medsci-agent/deepchem)<a href="https://agentmods.dev/skills/omar-a-hassan/medsci-agent/deepchem"><img src="https://agentmods.dev/badge/skills/omar-a-hassan/medsci-agent/deepchem/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/omar-a-hassan/medsci-agent/deepchem"><img src="https://agentmods.dev/badge/skills/omar-a-hassan/medsci-agent/deepchem.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00020 | $0.00445 |
| Opus 5 | $0.00010 | $0.00222 |
| Sonnet 5 | $0.00004 | $0.00089 |
| Haiku 4.5 | $0.00002 | $0.00044 |
Grade A, and why
deepchem scanned grade A with 0 findings 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 10d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
DeepChem
Overview
DeepChem is a Python library for molecular machine learning. It provides featurizers, datasets, model wrappers, and splitters for drug discovery and materials science tasks.
Featurizers
- ECFP (Extended Connectivity Fingerprints):
dc.feat.CircularFingerprint(size=1024, radius=2) - GraphConv:
dc.feat.ConvMolFeaturizer()-- converts molecules to graph objects. - Weave:
dc.feat.WeaveFeaturizer()-- atom and pair features. - RDKitDescriptors:
dc.feat.RDKitDescriptors()-- 200+ physicochemical descriptors.
Typical Workflow
import deepchem as dc
# Load or create dataset from SMILES
featurizer = dc.feat.CircularFingerprint(size=1024, radius=2)
loader = dc.data.CSVLoader(tasks=["activity"], feature_field="smiles", featurizer=featurizer)
dataset = loader.create_dataset("data.csv")
# Split
splitter = dc.splits.ScaffoldSplitter()
train, valid, test = splitter.train_valid_test_split(dataset)
# Train model
model = dc.models.MultitaskClassifier(n_tasks=1, n_features=1024, layer_sizes=[512, 256])
model.fit(train, nb_epoch=50)
# Evaluate
metric = dc.metrics.Metric(dc.metrics.roc_auc_score)
print(model.evaluate(test, [metric]))
Graph Convolutional Models
featurizer = dc.feat.ConvMolFeaturizer()
model = dc.models.GraphConvModel(n_tasks=1, mode="classification")
Key Details
- Splitters:
RandomSplitter,ScaffoldSplitter(preferred for generalization),ButinaSplitter. - MoleculeNet benchmarks available via
dc.molnet.load_*()(e.g.,load_tox21(),load_bbbp()). - Install:
pip install deepchem.
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.
- 10d ago First seen · 49 lines · 20 tokens per session scan A dc9d17257dae
deepchem is a skill published in the GitHub repository omar-A-hassan/medsci-agent (18 stars, last pushed 3d ago), licensed MIT. It adds 20 tokens to every session and 445 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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