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RooseveltAdvisors AI Skills

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浏览 RooseveltAdvisors 维护的已发布 AI 技能,比较用途与说明,并通过来源仓库了解安装方式。

作者统计

已收录技能

9

收录技能的仓库 Stars 合计

0

仓库 Forks

0

平均每个技能的仓库 Stars

0

同一仓库中的多个技能可能共享 Stars,合计包含重复仓库数据。

9 个技能

全部技能

GitHub

file-cleanup

RooseveltAdvisors

Session-based file cleanup for privacy compliance. Use to delete temporary files, uploaded clinical notes, generated outputs, and expired logs to maintain HIPAA-friendly operations.

GitHub

json-validation

RooseveltAdvisors

Pydantic schema validation for agent outputs. Use to validate JSON against TableOfContents, ClinicalSummary, TreatmentPlan, and EvaluatorFeedback schemas before accepting agent responses.

GitHub

structured-logging

RooseveltAdvisors

JSON-based structured logging for audit trails and debugging. Use for logging all agent operations, quality metrics, errors, and execution times with daily rotation and automatic cleanup.

GitHub

section-detection

RooseveltAdvisors

Detect clinical note sections (HPI, ROS, Assessment, Plan) using regex patterns and LLM topic segmentation. Generates ToC with accurate byte offsets.

GitHub

ollama-client

RooseveltAdvisors

Phi-4 LLM interaction skill for generating text completions via Ollama API. Use for all LLM inference tasks including section detection, summarization, recommendation generation, and quality evaluation.

GitHub

rag-retrieval

RooseveltAdvisors

Hybrid search (embedding + BM25) for retrieving relevant clinical note passages. Use for finding source evidence to support claims in summaries and recommendations.

GitHub

contextual-chunking

RooseveltAdvisors

Contextual Retrieval implementation for RAG - chunks clinical notes with LLM-generated context prepended to each chunk before embedding. Improves citation accuracy by 49% per Anthropic research.

GitHub

citation-extraction

RooseveltAdvisors

Extract and validate citations with Jaccard overlap calculation. Ensures all claims have verifiable source evidence with ≥0.7 alignment threshold.

GitHub

chroma-client

RooseveltAdvisors

ChromaDB vector database client for storing and retrieving text embeddings with hybrid search (dense + sparse). Use for RAG operations, contextual retrieval, and similarity search in clinical notes.

默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。