clinical-decision-support

clinical-decision-support is a skill for Claude Code from Zaoqu-Liu/ScienceClaw. It costs 97 tokens per session (6,054 once invoked), scanned A, a copy of clinical-decision-support, MIT.

A document-generation tool for clinical research and pharmaceutical decision support. It creates group-level patient analyses and evidence-based treatment recommendation reports as LaTeX or PDF documents.

In plain words
What is it for?
Use it to compare patient cohorts by biomarkers and outcomes, prepare treatment recommendations with evidence grading and decision algorithms, and produce publication-ready reports.
Why use it?
It organizes clinical evidence and study results into structured documents for research, guideline development, or regulatory work.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python scripts/generate_schematic.py "your diagram description" -o figures/output.png.

Good fit Use it to compare patient cohorts by biomarkers and outcomes, prepare treatment recommendations with evidence grading and decision algorithms, and produce publication-ready reports.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/Zaoqu-Liu/ScienceClaw
agentmods
npx agentmods add skills/zaoqu-liu/scienceclaw/clinical-decision-support

Made for: Claude Code.

Wrote 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.

agentmods badge for clinical-decision-support

README.md
[![agentmods](https://agentmods.dev/badge/skills/zaoqu-liu/scienceclaw/clinical-decision-support/github.svg)](https://agentmods.dev/skills/zaoqu-liu/scienceclaw/clinical-decision-support)
Your own site
<a href="https://agentmods.dev/skills/zaoqu-liu/scienceclaw/clinical-decision-support"><img src="https://agentmods.dev/badge/skills/zaoqu-liu/scienceclaw/clinical-decision-support/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.

agentmods 80×15 button for clinical-decision-support

Your own site · 80×15
<a href="https://agentmods.dev/skills/zaoqu-liu/scienceclaw/clinical-decision-support"><img src="https://agentmods.dev/badge/skills/zaoqu-liu/scienceclaw/clinical-decision-support.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 97 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,054 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 94% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00097 $0.06054
Opus 5 $0.00048 $0.03027
Sonnet 5 $0.00019 $0.01211
Haiku 4.5 $0.00010 $0.00605

Measured 10d ago against content hash dba3621421df, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

clinical-decision-support 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 10d 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.

Origin

This is a copy

94% identical to clinical-decision-support — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/clinical-decision-support/SKILL.md · 512 lines

How it starts

The opening of the file, as written. The whole thing — 512 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Clinical Decision Support Documents

Description

Generate professional clinical decision support (CDS) documents for pharmaceutical companies, clinical researchers, and medical decision-makers. This skill specializes in analytical, evidence-based documents that inform treatment strategies and drug development:

  1. Patient Cohort Analysis - Biomarker-stratified group analyses with statistical outcome comparisons
  2. Treatment Recommendation Reports - Evidence-based clinical guidelines with GRADE grading and decision algorithms

All documents are generated as publication-ready LaTeX/PDF files optimized for pharmaceutical research, regulatory submissions, and clinical guideline development.

Note: For individual patient treatment plans at the bedside, use the treatment-plans skill instead. This skill focuses on group-level analyses and evidence synthesis for pharmaceutical/research settings.

Writing Style: For publication-ready documents targeting medical journals, consult the venue-templates skill's medical_journal_styles.md for guidance on structured abstracts, evidence language, and CONSORT/STROBE compliance.

Capabilities

Document Types

Patient Cohort Analysis

  • Biomarker-based patient stratification (molecular subtypes, gene expression, IHC)
  • Molecular subtype classification (e.g., GBM mesenchymal-immune-active vs proneural, breast cancer subtypes)
  • Outcome metrics with statistical analysis (OS, PFS, ORR, DOR, DCR)
  • Statistical comparisons between subgroups (hazard ratios, p-values, 95% CI)
  • Survival analysis with Kaplan-Meier curves and log-rank tests
  • Efficacy tables and waterfall plots
  • Comparative effectiveness analyses
  • Pharmaceutical cohort reporting (trial subgroups, real-world evidence)

Treatment Recommendation Reports

  • Evidence-based treatment guidelines for specific disease states
  • Strength of recommendation grading (GRADE system: 1A, 1B, 2A, 2B, 2C)
  • Quality of evidence assessment (high, moderate, low, very low)
  • Treatment algorithm flowcharts with TikZ diagrams
  • Line-of-therapy sequencing based on biomarkers
  • Decision pathways with clinical and molecular criteria
  • Pharmaceutical strategy documents
  • Clinical guideline development for medical societies

Read the full file on GitHub · 512 lines

Changes

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.

  1. 10d ago First seen · 512 lines · 97 tokens per session scan A dba3621421df

Subscribe to this mod's changes

clinical-decision-support is a skill published in the GitHub repository Zaoqu-Liu/ScienceClaw (60 stars, last pushed 5mo ago), licensed MIT. It adds 97 tokens to every session and 6,054 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to clinical-decision-support, differing in 10 lines, and is treated as a copy.

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