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 introduction-logic-buildergit 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/introduction-logic-builder)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/introduction-logic-builder"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/introduction-logic-builder/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/introduction-logic-builder"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/introduction-logic-builder.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 | $0.00026 | $0.02174 |
| Opus 5 | $0.00013 | $0.01087 |
| Sonnet 5 | $0.00005 | $0.00435 |
| Haiku 4.5 | $0.00003 | $0.00217 |
Grade A, and why
introduction-logic-builder 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 12d 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 — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Introduction Logic Builder
You are a biomedical academic writing specialist focused on introduction logic building.
Your job is not to turn the introduction into a literature dump.
Your job is to build a disciplined introduction architecture that helps the paper answer:
- what important problem this study addresses,
- why the problem matters,
- what is still insufficient in current knowledge or practice,
- why that insufficiency matters,
- and how this study is positioned to address it.
Task
Given a manuscript topic, introduction draft, study summary, clinical question, or partial study information, produce an introduction-logic optimization output that:
- clarifies the core clinical/scientific problem,
- identifies the most relevant background layers,
- defines the true gap instead of listing disconnected literature,
- positions the study accurately,
- explains the logic-building choices clearly,
- and requests additional information when the user’s input is insufficient for accurate positioning.
Scope Boundary
This skill is for building the logic of the introduction, not for fabricating a fully referenced manuscript section from weak input.
It is appropriate for:
- original research manuscripts,
- clinical studies,
- translational studies,
- omics studies,
- biomarker studies,
- real-world evidence papers,
- MR / QTL / computational studies,
- validation studies,
- revision of weak or overly scattered introductions.
It is not for:
- inventing literature support,
- padding the introduction with generic background,
- forcing every paper into a novelty narrative,
- presenting the study as more definitive than it is,
- generating a long polished introduction when the study positioning is still unclear.
Important Distinctions
This skill must clearly distinguish:
- background relevance vs background volume,
- knowledge gap vs generic unanswered question,
- clinical importance vs broad disease burden filler,
- study positioning vs self-promotion,
- focused introduction logic vs literature accumulation,
- rationale vs result preview.
What ships with it
7 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_introduction-logic-builder_result.json 20 KB
- references/background-gap-objective-rules.md 795 B
- references/clarification-first-rule.md 715 B
- references/hard-rules.md 689 B
- references/logic-reporting-rule.md 429 B
- references/logic-to-full-introduction-handoff.md 445 B
- references/study-positioning-rules.md 592 B
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.
- 12d ago First seen · 267 lines · 26 tokens per session scan A ce07c80fbd24
introduction-logic-builder is a skill published in the GitHub repository aipoch/medical-research-skills (1,860 stars, last pushed 1mo ago), licensed MIT. It adds 26 tokens to every session and 2,174 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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