Skip to content
Autonomous Clinical AI Agent (Oncology) logo

Autonomous Clinical AI Agent (Oncology)

---name: autonomous-oncology-agent description: A multimodal precision oncology agent leveraging GPT-4 and vision transformers for cancer diagnosis, biomarker detection, and treatment planning. license: MIT metadata: author: Nature Cancer 2025 source: "https://www.nature.com/articles/s43018-025-0...

SKILL.md

Full skill instructions

"

Autonomous Clinical AI Agent (Oncology)

This skill implements the capabilities of the "Autonomous Clinical AI Agent" described in Nature Cancer (2025). It combines Large Language Models (LLMs) for reasoning with specialized vision models for pathology image analysis to support precision oncology decision-making.

When to Use This Skill

  • Precision Oncology: For interpreting complex cancer cases involving pathology, genomics, and clinical history.
  • Biomarker Detection: To identify status of key biomarkers (MSI, KRAS, BRAF) from pathology slides (H&E).
  • Guideline Adherence: To check treatment plans against NCCN or ASCO guidelines (via OncoKB/​PubMed).
  • Multimodal Synthesis: When you need to combine image data and text reports.

Core Capabilities

  1. Vision Transformer Analysis: Detects MSI status and key mutations (KRAS, BRAF) directly from H&E images.
  2. Clinical Reasoning: Synthesizes patient history, pathology, and genomics to recommend therapies.
  3. Evidence Retrieval: Integrates real-time knowledge from OncoKB and PubMed.
  4. Decision Support: Provides ranked treatment options with evidence levels.

Workflow

  1. Input Processing:
    • Text: Clinical notes, pathology reports, genomic panels.
    • Image: H&E histology slides.
  2. Analysis:
    • Vision model predicts molecular features from slides.
    • LLM extracts key clinical entities (Stage, Histology, Mutations).
  3. Reasoning:
    • Query OncoKB for actionable mutations.
    • Match against standard of care guidelines.
  4. Output: Generate a comprehensive "Tumor Board" style report.

Example Usage

User: "Review this case of metastatic colorectal cancer. The H&E slide is attached. What is the predicted MSI status and recommended first-line therapy?"

Agent Action:

  1. Runs vision model on H&E image -> Output: "MSI-High (Predicted)".
  2. Reads clinical notes -> "Patient is fit, ECOG 0."
  3. Consults Knowledge Base -> "MSI-High CRC responds to Pembrolizumab."
  4. Recommends: "Based on predicted MSI-High status, immunotherapy (Pembrolizumab) is recommended over standard chemotherapy..."

More Other skills

Delegate independent tasks to specialized agents working concurrently with isolated context.

295.4K 206.3K
View

Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.

179.7K 100.1K
View

Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.

179.7K 89.5K
View

A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).

179.7K 76.1K
View

Fundamental design principles for writing maintainable, testable Python code.

40.2K 21.9K
View

Modern responsive layouts using container queries, fluid typography, CSS Grid, and mobile-first strategies.

40.2K 20K
View

Generate Playwright tests from scenarios using interactive browser exploration and validation.

39.7K 18.2K
View

Modern React state management with Redux Toolkit, Zustand, Jotai, and React Query for every state category.

40.2K 14.7K
View

GDPR-compliant data handling with consent management, data subject rights, and privacy controls.

40.2K 14.3K
View

Python error handling patterns including input validation, exception hierarchies, and partial failure handling. Use when implementing validation logic, designing exception strategies, handling batch processing failures, or building robust APIs.

40.2K 13.5K
View

Detailed multi-file refactor planning with safety checks and rollback guidance.

39.7K 13K
View