--- name: autonomous-oncology-agent description: Precision Oncology keywords: - oncology - multimodal - H&E - biomarkers - NCCN measurable_outcome: Generate a prioritized treatment plan with evidence levels and predicted biomarker status (MSI/KRAS) within 5 minutes of data ingest. license: MIT metadata: author: Nature Cancer 2025 version: "1.0.0" compatibility: - system: Python 3.9+ allowed-tools: - run_shell_command - web_fetch --- # 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..." --- Source attribution: FreedomIntelligence Original project: https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 FridrichMethod Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. --- NOTE ON BUNDLED CONTENT This repository aggregates skills from multiple upstream projects (see the README for the source list). Each `skills//` directory may carry its own license inherited from its upstream source. The MIT license above applies to this repository's curation and the scripts/workflows in `/`, `/scripts/`, and `/.github/` — not to the upstream skill content itself. Consult the upstream repository linked in the README and any LICENSE file inside a skill directory before reusing skill content commercially. # Mega AI Hub resource metadata Creator / publisher: FreedomIntelligence Original project: https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills Attribution basis: Exact package in biomedical source index and publisher source table Fields of work: Data & Analytics, Healthcare & Life Sciences, Product Management Roles: Clinical Research, Data Scientist, Health Informatics, Medical Writer, Product Manager Specialties: Specialty not specified Tools: Oncokb, Pubmed, Python Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: ee072e53739c78bcf425bf9c90cbc9ae71de92c952c44c572a04d44a64320100 Metadata reviewed: 2026-10-27 This metadata supersedes earlier Mega AI Hub catalog attribution. Original instruction and supporting files are preserved.