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 learningmatter-mit/AtomisticSkills --skill drug-bioactivity-assaygit 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-bioactivity-assay)<a href="https://agentmods.dev/skills/learningmatter-mit/atomisticskills/drug-bioactivity-assay"><img src="https://agentmods.dev/badge/skills/learningmatter-mit/atomisticskills/drug-bioactivity-assay.svg" alt="Measured on agentmods" 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 | $0.00023 | $0.00662 |
| Opus 5 | $0.00012 | $0.00331 |
| Sonnet 5 | $0.00005 | $0.00132 |
| Haiku 4.5 | $0.00002 | $0.00066 |
Grade A, and why
drug-bioactivity-assay 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
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.
- 8d ago First seen · 70 lines · 23 tokens per session scan A 1ce5dd540511
drug-bioactivity-assay is a skill published in the GitHub repository learningmatter-mit/AtomisticSkills (161 stars, last pushed 4d ago), licensed MIT. It adds 23 tokens to every session and 662 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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