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Use this skill for requests related to LangGraph in order to fetch relevant documentation to provide accurate, up-to-date guidance.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.
Structured approach to exploratory data analysis with pandas, matplotlib, and seaborn. Use this skill when analyzing new datasets, understanding distributions, or preparing data for modeling.
Machine learning pipeline development with scikit-learn. Use this skill for training models, cross-validation, hyperparameter tuning, and model evaluation.
Write comprehensive clinical reports including case reports (CARE guidelines), diagnostic reports (radiology/pathology/lab), clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP, H&P, discharge summaries). Full support with templates, regulatory compliance (HIPAA, FDA, ICH-GCP), and validation tools.
Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.
Generate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.
| name | langgraph-docs |
| description | Use this skill for requests related to LangGraph in order to fetch relevant documentation to provide accurate, up-to-date guidance. |
This skill explains how to access LangGraph Python documentation to help answer questions and guide implementation.
Use the fetch_url tool to read the following URL: https://docs.langchain.com/llms.txt
This provides a structured list of all available documentation with descriptions.
Based on the question, identify 2-4 most relevant documentation URLs from the index. Prioritize:
Use the fetch_url tool to read the selected documentation URLs.
After reading the documentation, complete the users request.
