scientific-skills/Academic Writing/biomed-outline-generator/SKILL.md
Generates structured biomedical outlines for review articles, discussion sections, and thesis proposals. Use when a user provides biomedical keywords, results/discussion text, or a proposal title plus background and needs a directly usable academic writing scaffold.
npx skillsauth add aipoch/medical-research-skills biomed-outline-generatorInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
This is an Academic Writing skill for producing manuscript-grade biomedical outlines with deterministic headings and clear section logic.
If you want to confirm the local helper path exists before use:
python scripts/validate_skill.py --check
This helper is optional. The primary workflow is still direct outline generation from user input.
Use this skill in biomedical contexts when the user wants one of these three outputs:
Title: plus background, methods expectations, cohort notes, timeline, or validation requirementsRecommended:
Use this type when the input is mostly:
Signals:
Title:Use this type when the input contains:
Use this type when the input contains:
Title:If the request is off-domain, stop and use the refusal contract in ## Fallback and Refusal Contract.
Must include:
4-6 major chapters2-3 subchapters under each major chapter where appropriateMust include:
Must include:
#, ##, ###to be addedConfirm that:
Assign Type I, II, or III using the rules above.
Use the output contract for the detected type and keep section order deterministic.
For each section, add actionable subpoints that reflect:
Check that:
If the input is non-biomedical or too weak to classify, respond with:
Cannot generate a biomedical outline yet.
Reason: <non-biomedical input / insufficient context / unsupported request>
Accepted retry formats:
- Review: biomedical keywords or topic direction
- Discussion: biomedical results/discussion paragraph
- Proposal: `Title:` plus background and objectives
Research direction: tumor microenvironment, macrophage polarization, immune checkpoint resistance
Please generate a review outline.
In our mouse model, anti-PD-1 reduced tumor burden, but the effect was lost after CSF1 overexpression. Please draft a discussion outline.
Title: Exosomal miRNAs as early diagnostic biomarkers for Alzheimer's disease
Background: include plasma exosomes, qPCR versus small RNA-seq, validation cohort, and neuroinflammation markers.
tools
Generates complete conventional oncology bulk-transcriptome biomarker and hub-gene research designs from a user-provided cancer type and study direction. Always use this skill whenever a user wants to design, plan, or build a tumor bioinformatics study centered on differential expression, prognostic filtering or risk modeling, PPI-based hub-gene prioritization, diagnostic/prognostic evaluation, clinical association, immune infiltration context, methylation context, and optional tissue or cell validation. Covers five study patterns (signature-first prognostic workflow, hub-gene-first biomarker workflow, hybrid signature-to-hub workflow, immune-context biomarker workflow, translational validation workflow) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path...
development
Generates complete conventional non-oncology bioinformatics research designs from a user-provided disease context, process-related gene family or biological theme, and validation direction. Use when a study centers on multi-dataset bulk transcriptome integration, DEG analysis, process-gene intersection, enrichment analysis, GSEA, PPI hub-gene prioritization, TF/miRNA regulatory networks, ROC-based biomarker evaluation, and immune infiltration analysis. Covers five study patterns (process-DEG discovery, enrichment/GSEA interpretation, hub-gene prioritization, regulatory-network and immune interpretation, multi-layer public validation) and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.
tools
Plans confounder control, variable adjustment logic, and bias mitigation strategies at the protocol stage for clinical, epidemiologic, translational, observational, and biomarker studies. Always use this skill when a user needs to identify major confounders, decide which variables should or should not be adjusted for, compare matching/stratification/weighting approaches, anticipate selection or measurement bias, or pressure-test a study design before execution. Focus on bias sensing, causal structure awareness, variable-role classification, and critical design review rather than generic statistical advice.
testing
Generates complete comparative network-toxicology research designs from a user-provided exposure pair, shared toxic phenotype, and validation direction. Use when a study centers on two related exposures under one outcome and needs target collection, shared-vs-specific target decomposition, enrichment, PPI hub prioritization, docking, optional transcriptomic cross-checks, and conservative mechanistic synthesis. Covers five study patterns and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.