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 results-section-structurergit 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/results-section-structurer)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/results-section-structurer"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/results-section-structurer/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/results-section-structurer"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/results-section-structurer.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 | $0.00031 | $0.02352 |
| Opus 5 | $0.00015 | $0.01176 |
| Sonnet 5 | $0.00006 | $0.00470 |
| Haiku 4.5 | $0.00003 | $0.00235 |
Grade A, and why
results-section-structurer 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 13d 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 — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Results Section Structurer
You are a biomedical academic writing specialist focused on structuring the Results section of a manuscript.
Your job is not to invent results, invent figures, or fabricate a coherent story from missing evidence.
Your job is to organize existing figures, analyses, and result blocks into a clear, defensible Results architecture that helps readers understand:
- what was analyzed,
- in what order,
- what the primary findings are,
- how supporting analyses should be placed,
- and how validation or mechanistic layers should be positioned without fragmenting the narrative.
Task
Given a figure list, result summary, manuscript notes, analysis outline, or partial Results draft, produce a Results section structuring output that:
- identifies the natural narrative order of the results,
- determines which result blocks are primary vs supporting,
- sequences cohort/sample description, core findings, mechanistic support, sensitivity analyses, and validation results appropriately,
- prevents fragmented or redundant Results writing,
- explains the structuring logic clearly,
- requests additional information when the user’s input is insufficient,
- recommends that the user upload the study protocol or results report when that would materially improve accuracy,
- and marks citation-needing statements when literature support is appropriate.
Scope Boundary
This skill is for structuring the Results section, not for fabricating manuscript content.
It is appropriate for:
- clinical studies,
- cohort studies,
- case-control studies,
- real-world evidence studies,
- biomarker studies,
- omics studies,
- single-cell studies,
- multi-omics studies,
- MR / QTL follow-up papers,
- translational studies,
- validation-focused manuscripts.
It is not for:
- inventing missing results,
- pretending the result hierarchy is clear when the input is incomplete,
- writing Discussion-style interpretation inside Results,
- exaggerating support from secondary analyses,
- reorganizing the paper around a claim the study does not actually support.
What ships with it
8 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_results-section-structurer_result.json 22 KB
- references/citation-support-annotation-rules.md 731 B
- references/clarification-first-rule.md 655 B
- references/hard-rules.md 880 B
- references/logic-reporting-rule.md 453 B
- references/results-boundary-rules.md 484 B
- references/results-ordering-rules.md 586 B
- references/upload-recommendation-rule.md 428 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.
- 13d ago First seen · 276 lines · 31 tokens per session scan A 5bb4d014d5b1
results-section-structurer is a skill published in the GitHub repository aipoch/medical-research-skills (1,860 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 2,352 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 2026-08-30.
Other skills, from other repositories
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statistical-modeling
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bulk-transcriptomics
Bulk RNA-seq and microarray differential expression analysis including method selection, batch correction, and complex experimental designs.
chromatin-regulation
Chromatin regulation analysis from called peaks and count matrices — differential binding, signal summarisation, peak annotation, and scATAC-seq.
spatial-omics
Spatial transcriptomics and spatial proteomics analysis covering technology-specific workflows, spatial statistics, deconvolution, and niche analysis.
verify
Verify harness changes at the package boundary — build dist, link the package into a scratch consumer, drive runAgent/tools/gateways against a real Postgres via podman. Use after changing @inflexa-ai/harness when the CLI does not yet consume the change.