Medical Research Agent Skills is a library of agent instructions for medical and biomedical research, covering evidence analysis, study protocol design, data analysis, and academic writing. Researchers use it to guide compatible coding agents through common scientific workflows. The catalogue contains many of the library's skills and commands.
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 aipoch/medical-research-skills --skill non-tumor-mechanism-guided-diagnostic-ml-research-plannergit clone --depth 1 https://github.com/aipoch/medical-research-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/skills/aipoch/medical-research-skills/non-tumor-mechanism-guided-diagnostic-ml-research-planner)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/non-tumor-mechanism-guided-diagnostic-ml-research-planner"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/non-tumor-mechanism-guided-diagnostic-ml-research-planner/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/aipoch/medical-research-skills/non-tumor-mechanism-guided-diagnostic-ml-research-planner"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/non-tumor-mechanism-guided-diagnostic-ml-research-planner.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00135 | $0.03758 |
| Opus 5 | $0.00068 | $0.01879 |
| Sonnet 5 | $0.00027 | $0.00752 |
| Haiku 4.5 | $0.00014 | $0.00376 |
Grade A, and why
non-tumor-mechanism-guided-diagnostic-ml-research-planner 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 9d 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 — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Non-Tumor Mechanism-Guided Diagnostic ML Research Planner
You are an expert conventional non-oncology biomarker and diagnostic-model research planner.
Task: Generate a complete, structured research design — not a literature summary, not a tool list. A real, executable study plan with four workload options and a recommended primary path.
This skill is designed for article patterns like: public disease-expression dataset selection → optional multi-dataset merging and batch correction → optional mechanism-related gene-family retrieval → DEG analysis → candidate-set restriction → feature-selection pipeline → diagnostic model construction → ROC / calibration / DCA evaluation → immune / regulatory interpretation → optional orthogonal validation. Do not mechanically copy any anchor paper; generalize the pattern into a reusable conventional non-oncology mechanism-guided diagnostic-ML study-design framework.
This skill must follow the same output discipline and standardization style as the conventional-non-oncology-hub-gene-research-planner baseline: explicit scope control, four mandatory workload configurations, one recommended primary plan, dependency-aware workflow logic, a mandatory reference literature pack, and a fixed self-critical risk review immediately after the literature section.
Input Validation
Valid input: [disease / condition] + [goal] + optional [mechanism-related gene family / pathway / biological theme] + [validation direction]
Optional additions: public-data-only, GSEA interest, immune angle, TF/miRNA network interest, preferred config level, stricter feature-selection logic, batch-correction requirement, no wet lab.
Examples:
- "Diabetic foot ulcer with pyroptosis-related genes, need diagnostic model and references."
- "Chronic kidney disease plus oxidative stress theme, need ROC / calibration / DCA."
- "Non-oncology inflammatory disease with mechanism-guided feature selection and immune context."
- "Public multi-dataset diagnostic biomarker study with one external validation cohort."
What ships with it
9 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.
- eval_report_non-tumor-mechanism-guided-diagnostic-ml-research-planner_result.json 13 KB
- references/analysis-modules.md 2.9 KB
- references/figure-deliverable-plan.md 1.4 KB
- references/literature-retrieval-and-citation.md 2.0 KB
- references/method-library.md 2.7 KB
- references/study-patterns.md 1.2 KB
- references/validation-evidence-hierarchy.md 2.4 KB
- references/workflow-step-template.md 2.0 KB
- references/workload-configurations.md 3.7 KB
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.
- 9d ago First seen · 255 lines · 135 tokens per session scan A a46f18520d7b
non-tumor-mechanism-guided-diagnostic-ml-research-planner is a skill published in the GitHub repository aipoch/medical-research-skills (1,869 stars, last pushed today), licensed MIT. It adds 135 tokens to every session and 3,758 once invoked, about $0.0007 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 2026-09-03.
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Use when you have aligned ChIP-Seq reads (in BED or BEDPE format) and need to convert them into quantitative genome-wide signal tracks (coverage, p-value, or q-value scores) for downstream statistical comparison or peak detection.