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Found 96 Skills
Extract methodologies from documents or examples to create executable skills
Generate extractive summaries from long text documents. Control summary length, extract key sentences, and process multiple documents.
Implement optimal chunking strategies in RAG systems and document processing pipelines. Use when building retrieval-augmented generation systems, vector databases, or processing large documents that require breaking into semantically meaningful segments for embeddings and search.
Automate payer review of prior authorization (PA) requests. This skill should be used when users say "Review this PA request", "Process prior authorization for [procedure]", "Assess medical necessity", "Generate PA decision", or when processing clinical documentation for coverage policy validation and authorization decisions.
Translate academic papers from arXiv to Chinese. Use when users want to (1) translate arXiv papers from English to Chinese, or (2) create technical reports summarizing academic papers. Works with arXiv paper IDs like "2206.04655".
Use Desktop Commander MCP (typically tools like `mcp__desktop-commander__*`) to manage local files and long-running processes: read/write/search files, apply precise edits, work with Excel/PDFs, run terminal commands and interact with REPLs (Python/Node/SSH/DB), inspect/terminate processes, and review tool call history. Use when the task requires doing real work on the machine (editing code/configs, searching a repo, analyzing CSV/Excel, generating/modifying PDFs, running commands with streaming output).
Integrate with Affinda's document AI API to extract structured data from documents (invoices, resumes, receipts, contracts, and custom types). Covers authentication, client libraries (Python, TypeScript), structured outputs with Pydantic models and TypeScript interfaces, webhooks, upload patterns, and the full documentation map. Use when building integrations that parse, classify, or extract data from documents using Affinda.
Build a section-by-section claim–evidence matrix (`outline/claim_evidence_matrix.md`) from the outline and paper notes. **Trigger**: claim–evidence matrix, evidence mapping, 证据矩阵, 主张-证据对齐. **Use when**: 写 prose 之前需要把每个小节的可检验主张与证据来源显式化（outline + paper notes 已就绪）。 **Skip if**: 缺少 `outline/outline.yml` 或 `papers/paper_notes.jsonl`。 **Network**: none. **Guardrail**: bullets-only（NO PROSE）；每个 claim 至少 2 个证据来源（或显式说明例外）。
Convert text with private context or internal dependencies into generic, unbiased expressions. Use for project decontextualization (handoff, open-source prep), methodology abstraction, cross-team sharing, anonymization. Includes path strings and file/folder names as they appear in text.
Converts PDF pages to images and uses vision analysis to extract content including diagrams, charts, and visual elements. Use for PDFs with rich visual content. Requires pdf2image and poppler-utils.
Guidance for processing financial documents (invoices, receipts, statements) with OCR and text extraction. This skill should be used when tasks involve extracting data from financial PDFs or images, generating summaries (CSV/JSON), or moving/organizing processed documents. Emphasizes data safety practices to prevent catastrophic data loss.
Convert each page of a PDF file into image files; supports custom image formats (PNG/JPG) and resolution; suitable for scenarios such as document processing and image-based archiving