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 PKU-YuanGroup/OpenAI4S --skill bio-clinical-databases-msi-detectiongit clone --depth 1 https://github.com/PKU-YuanGroup/OpenAI4SWrote 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/pku-yuangroup/openai4s/bio-clinical-databases-msi-detection)<a href="https://agentmods.dev/skills/pku-yuangroup/openai4s/bio-clinical-databases-msi-detection"><img src="https://agentmods.dev/badge/skills/pku-yuangroup/openai4s/bio-clinical-databases-msi-detection/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/pku-yuangroup/openai4s/bio-clinical-databases-msi-detection"><img src="https://agentmods.dev/badge/skills/pku-yuangroup/openai4s/bio-clinical-databases-msi-detection.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 | $0.00134 | $0.05633 |
| Opus 5 | $0.00067 | $0.02816 |
| Sonnet 5 | $0.00027 | $0.01127 |
| Haiku 4.5 | $0.00013 | $0.00563 |
Grade A, and why
bio-clinical-databases-msi-detection 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.
This is a copy
97% identical to bio-clinical-databases-msi-detection — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 356 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: MSIsensor-pro 1.2+, MSIsensor 0.6+, MANTIS 1.0.5+, samtools 1.19+, mSINGS 5.6+, pandas 2.2+, cyvcf2 0.30+. FDA pembrolizumab MSI-H / dMMR pan-tumor approval is from 2017 (Le 2015 NEJM; KEYNOTE-016/164/158); approval extended to colorectal first-line in 2020.
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show <package>thenhelp(module.function)to check signatures - CLI:
<tool> --version
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. MSIsensor-pro replaces MSIsensor for tumor-only assays; MSIsensor-ct is the bTMB-equivalent for ctDNA panels.
MSI Detection; The Companion ICI Biomarker to TMB
'Detect MSI status from this somatic sequencing data' -> Profile microsatellite instability across canonical loci (Bethesda 5 panel + extended NGS-derived sites); classify MSI-H / MSS / MSI-L per Bethesda / FDA / KEYNOTE convention.
- CLI (recommended tumor-only):
msisensor-pro msi -d microsatellites.list -t tumor.bam -o msi_out -b 16 - CLI (paired tumor-normal):
msisensor msi -d microsatellites.list -n normal.bam -t tumor.bam -o msi_out - CLI (ctDNA / blood MSI):
msisensor-ct ... - CLI (older WES standard):
mantis -t tumor.bam -n normal.bam -b targets.bed --threads 8
The Regulatory and Trial Landscape
| Event | Year | Threshold | Notes |
|---|---|---|---|
| Le 2015 NEJM | 2015 | MSI-H + ICI in CRC | The seminal paper: pembrolizumab in MSI-H CRC ORR 40% vs 0% MSS |
| FDA pembrolizumab MSI-H / dMMR pan-tumor | 2017 | MSI-H | First tissue-agnostic FDA approval (KEYNOTE-016/164/158) |
| FDA pembrolizumab first-line MSI-H CRC | 2020 | MSI-H + first-line CRC | KEYNOTE-177 |
| CheckMate 142 | 2017-2018 | MSI-H + nivolumab/ipilimumab | Pan-tumor MSI-H second-line |
| ESMO 2024 | 2024 | MSI-H | Maintained pan-tumor MSI-H biomarker |
| Universal Lynch screening | -- | IHC + MSI on all CRC <= 70 yr | NCCN / ACG / EGAPP guidelines |
What ships with it
2 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 · 356 lines · 134 tokens per session scan A 85a54efd8ffa
bio-clinical-databases-msi-detection is a skill published in the GitHub repository PKU-YuanGroup/OpenAI4S (407 stars, last pushed today), licensed MIT. It adds 134 tokens to every session and 5,633 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to bio-clinical-databases-msi-detection, differing in 12 lines, and is treated as a copy.
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