clinical-decision-support
Generate Clinical Decision Support Reports
Clinical research teams need consistent evidence summaries, biomarker analyses, and treatment algorithms. This skill creates structured CDS reports with statistics, GRADE evidence grading, and publication-ready LaTeX formatting.
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Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "clinical-decision-support" from https://skillstore.io/skills/k-dense-ai-clinical-decision-support.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-clinical-decision-support/manifest. Verify the artifact. Stop and obtain explicit user consent before installing or changing files.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "clinical-decision-support". A request to compare 60 HER2-positive metastatic breast cancer patients by hormone receptor status.
Expected outcome:
A structured cohort analysis with an executive summary, biomarker subgroup table, response outcomes, survival interpretation, limitations, and clinical implications.
Using "clinical-decision-support". A request for advanced NSCLC recommendations using PD-L1, EGFR, ALK, and performance status.
Expected outcome:
A treatment recommendation report with GRADE ratings, biomarker-directed therapy sequencing, evidence tables, safety monitoring, and a decision pathway.
Using "clinical-decision-support". A request to validate a draft clinical decision support document before sharing.
Expected outcome:
A review summary covering missing sections, citation gaps, statistical reporting issues, possible identifiers, and biomarker nomenclature concerns.
Security Audit
High RiskMost static findings are false positives from clinical terminology, markdown code fences, TikZ style syntax, and Python list operations. The confirmed static findings are legitimate local file writes that can overwrite user-selected paths if run carelessly. Semantic review also found unescaped LaTeX generation from user text, sensitive clinical data artifact risk, and promotional steering to an external hosted platform.
Confirmed security concerns (3)
Capability review items (9)
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
Risk Factors
📁 Filesystem access (29)
🔑 Env variables (1)
⚙️ External commands (41)
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https://skillstore.io/skills/k-dense-ai-clinical-decision-support/audits/7?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_reportMarkdown badge
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<a href="https://skillstore.io/skills/k-dense-ai-clinical-decision-support?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/k-dense-ai-clinical-decision-support/security.svg" alt="Skillstore security assessment" loading="lazy"></a>Embed card
<iframe src="https://skillstore.io/embed/skills/k-dense-ai-clinical-decision-support.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
K-Dense-AI. (2026). clinical-decision-support security audit report (audit version 7) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-clinical-decision-support/audits/7BibTeX citation
@techreport{k-dense-ai-k-dense-ai-clinical-decision-support-2026,
author = {K-Dense-AI},
title = {clinical-decision-support security audit report (audit version 7)},
institution = {Skillstore},
year = {2026},
number = {7},
url = {https://skillstore.io/skills/k-dense-ai-clinical-decision-support/audits/7},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "clinical-decision-support security audit report (audit version 7)"
version: "unspecified"
type: report
authors:
- name: "K-Dense-AI"
date-released: "2026-07-05"
url: "https://skillstore.io/skills/k-dense-ai-clinical-decision-support/audits/7"
identifiers:
- type: other
value: "skillstore:k-dense-ai-clinical-decision-support:audit:7"
description: "Skillstore immutable audit report identifier"
Compare variants
2 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
k-dense-ai-clinical-decision-support
2026-08-21
davila7-clinical-decision-support
2026-08-21
Skillstore Score
Why this score Evidence Confidence: MediumWhat You Can Build
Summarize Biomarker-Stratified Trial Outcomes
Create a cohort analysis comparing outcomes across biomarker-defined patient groups, with tables and statistical interpretation.
Draft Evidence-Graded Treatment Guidance
Prepare a treatment recommendation report that links therapies, biomarkers, evidence quality, and monitoring considerations.
Prepare Decision Algorithms for Review
Generate a structured treatment pathway with decision points, supporting evidence, and publication-ready flowchart guidance.
Try These Prompts
Generate a clinical cohort summary for de-identified patients with disease type, biomarker groups, treatments, response rates, PFS, OS, and key limitations.
Create a biomarker-stratified cohort analysis comparing group outcomes. Include baseline characteristics, ORR, DCR, median PFS, median OS, hazard ratios, p-values, and interpretation.
Prepare evidence-based treatment recommendations for the specified disease state. Grade each recommendation using GRADE, cite key trials or guidelines, and include monitoring requirements.
Generate a full clinical decision support document with page-one executive summary, evidence review, biomarker-guided algorithm, treatment sequencing, statistical tables, limitations, and review checklist.
Best Practices
- Use de-identified inputs and remove HIPAA identifiers before generating or validating documents.
- Provide source evidence, assay methods, cut points, follow-up time, and statistical assumptions.
- Review all recommendations, LaTeX, and figures with qualified clinical and regulatory experts.
Avoid
- Do not use generated recommendations as direct bedside orders or individual patient treatment plans.
- Do not compile untrusted LaTeX with shell escape or permissive file access.
- Do not publish outputs without checking citations, statistics, conflicts of interest, and data privacy.
Frequently Asked Questions
Is this skill for individual patient care?
Can it generate statistical tables and survival summaries?
Does it automatically verify current medical guidelines?
Can it handle protected health information?
What formats does it target?
Why does this skill need security review?
Developer Details
Author
K-Dense-AILicense
MIT License
Skillstore revision
r1
Version notice
The author did not declare a version.
Ref
a25199bc7d6b82598536822d1738eb5d5f54025b
Maintenance freshness
7/18/2026
Usage
10 downloads · 238 views
File structure