Install
$ agentstack add skill-learningmatter-mit-atomisticskills-drug-bioactivity-assay ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Bioactivity and Assay Data Retrieval
Goal
To programmatically retrieve the testing history of a specific chemical compound against biological targets using PubChem's Assay Summary endpoint. This skill allows filtering for "Active" outcomes, providing assay IDs (AIDs), target GeneIDs, and micromolar activity values to assess a compound's promiscuity or target specificity.
Instructions
1. Extract All Assays
Retrieve all assays for a given compound (CID), regardless of outcome:
# Env: base-agent
python .agents/skills/drug-bioactivity-assay/scripts/get_assays.py \
--cid 2244 \
--limit 50 \
--outdir research/aspirin_assays \
--output aspirin_all_assays.json
2. Extract Only 'Active' Results
Use the --active_only flag to strictly return assays where the compound was marked as "Active" or showed positive binding/inhibition.
# Env: base-agent
python .agents/skills/drug-bioactivity-assay/scripts/get_assays.py \
--cid 5291 \
--active_only \
--limit 50 \
--outdir research/imatinib_assays \
--output imatinib_active_assays.json
Parameters:
--cid: PubChem CID of the target molecule (e.g., 5291 for Imatinib).--outdir: Directory to save the resulting JSON file.--active_only: (Optional) Flag to strictly filter results to assays where the test outcome was "Active".--limit: (Optional) Maximum number of assays to retrieve (default: 1000) to keep JSON sizes manageable.--output: (Optional) Output filename (default:assay_summary.json).
Examples
We can test extracting known active targets for the cancer drug Imatinib (CID: 5291).
# Env: base-agent
python .agents/skills/drug-bioactivity-assay/scripts/get_assays.py \
--cid 5291 \
--active_only \
--limit 20 \
--outdir .agents/skills/drug-bioactivity-assay/examples/imatinib \
--output assays_imatinib_active.json
Constraints
- Assay Availability: Compounds with no biological testing history in PubChem will return 0 results.
- Reporting Variations: High-throughput screening (HTS) assay results often lack explicit target GeneIDs or quantitative Activity Values compared to confirmatory literature assays. The script retrieves whatever is available natively in the column.
- Network Limits: PubChem can sporadically drop connections when rendering very large assay summaries. The script automatically handles connection drops and
HTTP 503blocking via exponential backoff.
Author: Bowen Deng Contact: GitHub @learningmatter-mit
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: learningmatter-mit
- Source: learningmatter-mit/AtomisticSkills
- License: MIT
- Homepage: https://arxiv.org/abs/2605.24002
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.