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.
git clone --depth 1 https://github.com/zamushwani/biomedical-ai-skillsWrote 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/commands/zamushwani/biomedical-ai-skills/deconvolve-immune)<a href="https://agentmods.dev/commands/zamushwani/biomedical-ai-skills/deconvolve-immune"><img src="https://agentmods.dev/badge/commands/zamushwani/biomedical-ai-skills/deconvolve-immune/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/commands/zamushwani/biomedical-ai-skills/deconvolve-immune"><img src="https://agentmods.dev/badge/commands/zamushwani/biomedical-ai-skills/deconvolve-immune.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 | $0.00039 | $0.00302 |
| Opus 5 | $0.00019 | $0.00151 |
| Sonnet 5 | $0.00008 | $0.00060 |
| Haiku 4.5 | $0.00004 | $0.00030 |
Grade A, and why
deconvolve-immune 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 11d 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
Estimate immune composition for $0 using method $1 (default: quanTIseq).
Follow the immune-deconvolution skill. The parts that are usually got wrong:
- Method dictates the input scale. quanTIseq and CIBERSORT expect TPM; some methods want un-logged values. Feeding log-TPM where TPM is expected produces plausible-looking, wrong fractions.
- Know what the output means. quanTIseq and EPIC give fractions comparable across cell types within a sample; xCell and MCP-counter give scores comparable across samples within a cell type. Comparing an xCell score between two cell types is meaningless.
- Correct for tumour purity where it matters — immune fractions are diluted by tumour content, so a purity difference between groups masquerades as an immune difference.
- Run more than one method and report where they disagree. Agreement across methods is the only cheap validation available.
Report: the fraction/score matrix, which method and input scale were used, and a cross-method comparison for the key cell types.
If $0 is empty, ask for the expression matrix.
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.
- 11d ago First seen · 19 lines · 0 tokens per session scan A f3d6067f89e9
deconvolve-immune is a command published in the GitHub repository zamushwani/biomedical-ai-skills (1 stars, last pushed 12d ago), licensed MIT. It adds 39 tokens to every session and 302 once invoked, about $0.0002 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 2026-08-31.
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