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Found 53 Skills
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.
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
Summarize documents, extract key points, and generate structured outlines
Markdown 파일을 한글 문서(HWPX)로 변환합니다. pypandoc-hwpx 기반.
한글(HWP/HWPX) 문서를 다양한 포맷(Text, HTML, ODT, PDF)으로 변환하고, Markdown/HTML을 HWPX로 생성하는 작업을 도와줍니다. LLM/RAG 파이프라인을 위한 문서 처리, 청킹, LangChain 연동을 지원합니다.
Reads images of payment statements and returns structured data. It can be called by other skills or directly by users.
Reads images of withholding tax slips and returns structured data. It can be called by other skills or directly by users.
Optimize the content of Official Accounts articles in local Markdown files to make them more suitable for Chinese users aged 16-50 to read on the WeChat Official Accounts Platform. It supports optimizing article structure, language expression, and typography, as well as improving opening attractiveness, paragraph rhythm, and end conversion. This skill is applicable when users need to optimize Official Accounts articles, improve Markdown content quality, and enhance article reading experience.