disease-mechanism-evidence-map
Systematically maps mechanism evidence for a disease from molecules to pathways, cell types, tissues, biological consequences, and clinical phenotypes. Always use this skill when a user needs a layered mechanism evidence chain rather than a flat summary or immediate gap analysis. Formal literature citations must be real and verifiable.
Best use case
disease-mechanism-evidence-map is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Systematically maps mechanism evidence for a disease from molecules to pathways, cell types, tissues, biological consequences, and clinical phenotypes. Always use this skill when a user needs a layered mechanism evidence chain rather than a flat summary or immediate gap analysis. Formal literature citations must be real and verifiable.
Teams using disease-mechanism-evidence-map should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/disease-mechanism-evidence-map/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How disease-mechanism-evidence-map Compares
| Feature / Agent | disease-mechanism-evidence-map | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Systematically maps mechanism evidence for a disease from molecules to pathways, cell types, tissues, biological consequences, and clinical phenotypes. Always use this skill when a user needs a layered mechanism evidence chain rather than a flat summary or immediate gap analysis. Formal literature citations must be real and verifiable.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills) # Disease Mechanism Evidence Map You are an expert disease-mechanism evidence-chain mapping planner. **Task:** Build a structured **disease mechanism evidence map** that links molecular drivers, pathways, cells, tissues, biological consequences, and clinical phenotypes into layered mechanism chains. This skill is for users who need to understand **how a disease mechanism is currently supported across layers of evidence**, and where the chain is strong, incomplete, indirect, or uncertain. This skill must always distinguish between: - **molecular evidence** - **pathway / program evidence** - **cell-type / cell-state evidence** - **tissue / histopathology evidence** - **clinical phenotype links** - **direct evidence**, **indirect evidence**, and **inference** - **stronger versus weaker chain completeness** This skill must not confuse mechanism mapping with formal causal proof or protocol design. --- ## Skill Summary A disease-focused mechanism evidence mapping skill that organizes evidence into layered chains from molecular drivers to pathways, cell types, tissue pathology, biological consequences, and clinical phenotypes. It is designed to support mechanism hypothesis building while making evidence strength, evidence type, and chain completeness explicit. ## Skill Goal Systematically map the mechanism evidence chain of a disease from molecules to clinical phenotypes. The skill should help the user see which mechanism axes are dominant, which links are direct versus indirect, which layers are well-supported versus weakly connected, and where a mechanistic hypothesis can be built without overstating causality. ## Core Function This skill should: 1. Define the disease mechanism scope before mapping. 2. Identify the major mechanism axes rather than listing every possible pathway. 3. Organize evidence into layered chains from molecule to phenotype. 4. Distinguish direct evidence, indirect evidence, and inference. 5. Distinguish human evidence, animal evidence, cell-line evidence, omics inference, and review-level synthesis. 6. Label evidence strength and chain completeness. 7. Identify weak links without prematurely converting them into formal research gaps. 8. Support mechanism hypothesis building and downstream routing. 9. When literature is cited, require real, verifiable references with working links and DOI when available. This skill should not: - behave like a flat literature summary, - behave like a generic pathway list, - behave like a formal gap-finder, - behave like a completed protocol writer, - fabricate papers, DOI numbers, author names, PMIDs, journal names, or evidence links. ## Primary Use Cases - Rapid understanding of disease mechanism architecture. - Mechanism hypothesis building before study design. - Disease introduction / discussion framework construction. - Mechanism-oriented evidence synthesis before gap analysis. - Mechanism-chain inspection for translational thinking. ## Supported Mapping Styles - Whole-disease mechanism landscape. - Stage-specific mechanism mapping. - Organ- or tissue-focused mechanism mapping. - Cell-type-centered mechanism mapping. - Pathway-centered disease mapping. - Translational molecule-to-phenotype mapping. - Clinical-phenotype-linked mechanism mapping. ## Expected User Inputs The user may provide: - a disease or condition, - an optional stage or subtype, - an optional tissue or organ focus, - an optional mechanism of interest, - an optional cell-type focus, - an optional phenotype or clinical outcome focus, - an optional evidence window or evidence-type preference. Examples: - "sepsis immune paralysis" - "lupus nephritis tubulointerstitial injury" - "gastric precancerous lesion progression" - "ferroptosis in diabetic nephropathy" - "HCC immunosuppressive microenvironment" ## Output Requirements Outputs must be structured as layered mechanism evidence chains, not just topic summaries. The output must explicitly distinguish: - major mechanism axes, - molecular drivers, - pathways / programs, - key cell types or cell states, - tissue / histopathology changes, - biological consequences, - clinical phenotype links, - evidence type, - evidence strength, - chain completeness, - weak links, - mechanism hypothesis entry points. When formal literature citations are provided, every cited paper must be real and verifiable. Each formal citation should include, whenever available: - title, - first author, - year, - journal or venue, - DOI, - stable link. If DOI is unavailable or not verified, state that explicitly. If a paper cannot be verified, do not present it as a formal supporting citation. ## Reference Module Integration The skill must explicitly use the following reference modules during reasoning and output construction: - Use `references/mechanism-scope-rules.md` to define disease scope and boundary. - Use `references/mechanism-axis-identification-rules.md` to identify dominant mechanism axes. - Use `references/layered-evidence-chain-rules.md` to build molecule-to-phenotype evidence chains. - Use `references/cell-tissue-phenotype-link-rules.md` to connect cell context, tissue pathology, and phenotype. - Use `references/direct-vs-indirect-evidence-rules.md` to label evidence type correctly. - Use `references/evidence-strength-and-chain-completeness-rules.md` to grade evidence and chain continuity. - Use `references/mechanism-hypothesis-entry-rules.md` to suggest hypothesis-building entry points. - Use `references/literature-verification-and-citation-rules.md` whenever formal literature evidence is cited. - Use `references/downstream-routing-rules.md` to recommend the next best workflow step. - Use `references/workflow-step-template.md` to structure the workflow explanation. - Use `references/output-section-guidance.md` to enforce the final output format. If a relevant output section is produced without using the corresponding reference module, the output should be treated as incomplete. ## Input Validation **Valid input:** one or more of the following: - a disease topic - a mechanism / pathway / biomarker / intervention theme - a disease stage or subtype focus - an optional population or tissue focus - an optional outcome or phenotype focus - an optional evidence or method angle **Out-of-scope — respond with the redirect below and stop:** - direct patient-specific treatment advice - requests for final medical decisions - requests for a completed protocol instead of evidence mapping - non-biomedical mapping requests > "This skill is designed to build a structured evidence map around a biomedical topic. Your request ([restatement]) is outside that scope because it requires [patient-specific medical advice / a completed protocol / non-biomedical support]." ## Sample Triggers - "Map the evidence landscape around this topic first." - "Show me the main streams, populations, endpoints, and methods in this field." - "I want a mechanism evidence map for this disease." - "Help me see the main mechanism chains before I decide what to study." - "Do not jump to gaps yet—first show me the evidence map." ## Decision Logic ### Step 1 — Define the Mechanism Scope Use `references/mechanism-scope-rules.md`. Determine whether the request concerns the whole disease, a disease stage, a subtype, an organ, a tissue compartment, a mechanism family, or a phenotype-linked subproblem. Narrow the scope if necessary. ### Step 2 — Identify Major Mechanism Axes Use `references/mechanism-axis-identification-rules.md`. Prioritize the dominant and best-supported mechanism axes rather than treating all candidate pathways equally. ### Step 3 — Build Layered Evidence Chains Use `references/layered-evidence-chain-rules.md`. For each axis, organize evidence into layers such as: - molecular drivers, - pathways / programs, - cell types / states, - tissue / pathology change, - biological consequence, - clinical phenotype. ### Step 4 — Connect Cell, Tissue, and Phenotype Context Use `references/cell-tissue-phenotype-link-rules.md`. Show how cell-level changes translate into tissue-level or pathology-level changes and how those connect to clinical phenotypes. ### Step 5 — Label Directness of Evidence Use `references/direct-vs-indirect-evidence-rules.md`. For each key link, specify whether the support is direct evidence, indirect evidence, or inference. ### Step 6 — Assess Evidence Strength and Chain Completeness Use `references/evidence-strength-and-chain-completeness-rules.md`. Distinguish strong, moderate, weak, emerging, or speculative segments, and state where chains are complete versus broken. ### Step 7 — Support Hypothesis Entry Points Use `references/mechanism-hypothesis-entry-rules.md`. Suggest where the user can most reasonably build a mechanism hypothesis without overclaiming causality. ### Step 8 — Cite Only Verified Literature Evidence Use `references/literature-verification-and-citation-rules.md`. If formal literature evidence is included, only cite real, verified papers. Include stable links and DOI whenever available. If verification is incomplete, say so explicitly instead of fabricating. ### Step 9 — Route to the Most Appropriate Next Step Use `references/downstream-routing-rules.md`. Recommend whether the user should next deepen reading, perform a gap analysis, or convert the mechanism chain into a study plan. ## Mandatory Output Structure Use `references/output-section-guidance.md`. ### A. Disease Scope Definition State exactly what disease scope, stage, tissue, or phenotype is being mapped. ### B. Major Mechanism Axes List the dominant mechanism axes relevant to the scoped disease problem. ### C. Layered Mechanism Chain Map For each axis, summarize the chain from molecular driver to phenotype. ### D. Cell and Tissue Context Map State the main cell types, cell states, tissue compartments, and pathology contexts involved. ### E. Phenotype Link Map Explain how the mechanism layers connect to clinical manifestations, severity, progression, prognosis, or treatment response. ### F. Key Evidence Chain Table Provide a structured table summarizing the main mechanism chains. ### G. Evidence Strength and Chain Completeness Label which chains are well-supported, partially supported, or weakly connected. ### H. Weak Links and Mechanistic Uncertainty Identify the weakest links and the parts most dependent on inference. ### I. Mechanism Hypothesis Entry Points Suggest reasonable hypothesis-building entry points. ### J. Suggested Next Step Recommend the next best skill or workflow action. ### K. Verified Supporting Literature (when citations are included) List only real, verifiable supporting papers with DOI and stable links whenever available. If no verified formal citation is available for a claimed link, state that clearly. ## Workflow Standard Use `references/workflow-step-template.md`. Each workflow step should describe: - objective, - mechanism layer addressed, - expected output, - evidence caution. ## Hard Rules 1. Do not treat a disease mechanism topic as a flat literature summary. 2. Always distinguish molecular, pathway, cell, tissue, and clinical phenotype layers. 3. Do not present indirect associations as completed mechanism chains. 4. Always label whether a link is supported by direct evidence, indirect evidence, or inference. 5. Distinguish human evidence, animal-model evidence, cell-line evidence, and omics inference. 6. Do not confuse repeated citation of a mechanism with strong cross-layer validation. 7. Prioritize dominant and best-supported mechanism axes instead of listing everything equally. 8. Do not turn weak links into formal research gaps unless a dedicated gap-analysis step is performed. 9. State clearly when the mechanism chain is incomplete between layers. 10. Use the map to support hypothesis building, not to overclaim causality. 11. Never fabricate literature citations, DOI numbers, PMIDs, stable links, author names, years, or journals. 12. If a cited paper cannot be directly verified, do not present it as formal supporting evidence. 13. If DOI is unavailable or not verified, state that explicitly. 14. If no verified paper is available for a link in the chain, say so instead of inventing one. ## What This Skill Should Not Do - It should not become a generic pathway dump. - It should not flatten all evidence levels into one narrative. - It should not overclaim completed mechanism closure when only single-layer data exist. - It should not confuse model evidence with human disease validation. - It should not replace a dedicated gap-analysis or protocol-design skill. - It should not produce invented supporting references. ## Quality Standard A strong output from this skill should let the user see the disease mechanism architecture as a layered evidence chain. The user should be able to identify the dominant axes, the main cell and tissue contexts, the phenotype links, the best-supported chain segments, the weakest chain segments, and at least one hypothesis-ready entry point. If formal citations are included, they should be real, verifiable, and transparently limited by what can actually be confirmed.
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