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Found 7 Skills
Ingests unstructured and semi-structured documents into Neo4j as a knowledge graph. Use when chunking PDFs, HTML, plain text, or Markdown; extracting entities and relationships from text with an LLM (SimpleKGPipeline, neo4j-graphrag); loading JSON via apoc.load.json; building Document→Chunk→Entity graph structures; or connecting LangChain/LlamaIndex document loaders to Neo4j. Covers neo4j-graphrag SimpleKGPipeline, LLM Graph Builder web UI, entity resolution, chunking strategies, and graph schema design for RAG pipelines. Does NOT handle structured CSV/relational import — use neo4j-import-skill. Does NOT handle GraphRAG retrieval after ingestion — use neo4j-graphrag-skill. Does NOT handle vector index creation — use neo4j-vector-search-skill.
Build GraphRAG retrieval pipelines on Neo4j using the neo4j-graphrag Python package (formerly neo4j-genai). Covers retriever selection (VectorRetriever, HybridRetriever, VectorCypherRetriever, HybridCypherRetriever, Text2CypherRetriever), retrieval_query Cypher fragments, query_params, pipeline wiring (GraphRAG + LLM), embedder setup, index creation, and LangChain/LlamaIndex integration. Does NOT handle KG construction from documents — use neo4j-document-import-skill. Does NOT handle plain vector search — use neo4j-vector-index-skill. Does NOT handle GDS analytics — use neo4j-gds-skill. Does NOT handle agent memory — use neo4j-agent-memory-skill.
Import structured data into Neo4j — LOAD CSV, CALL IN TRANSACTIONS, neo4j-admin database import full (offline bulk), apoc.load.csv/json, apoc.periodic.iterate, driver batch writes. Covers method selection, header file format, type coercion, null handling, ON ERROR modes, CONCURRENT TRANSACTIONS, pre-import constraint setup, and post-import validation. Use when importing CSV/JSON/Parquet files, migrating relational data to graph, or bulk-loading large datasets. Does NOT handle unstructured document/PDF/vector chunking pipelines — use neo4j-document-import-skill. Does NOT handle live app write patterns (MERGE/CREATE) — use neo4j-cypher-skill. Does NOT handle neo4j-admin backup/restore/config — use neo4j-cli-tools-skill.
Ingest any raw text data, conversation logs, chat exports, or unstructured documents into the Obsidian wiki. Use this skill when the user wants to process data that isn't standard documents or Claude history — things like ChatGPT exports, Slack threads, Discord logs, meeting transcripts, journal entries, CSV data, browser bookmarks, email archives, or any raw text dump. Triggers on "ingest this data", "process these logs", "add this export to the wiki", "import my chat history from X". This is the catch-all for any text source not covered by the more specific ingest skills.
Implements the Syncfusion Angular Rich Text Editor (ejs-richtexteditor) from @syncfusion/ej2-angular-richtexteditor using RichTextEditorModule, HtmlEditorService, and MarkdownEditorService.Use this skill for toolbar configuration, image/video/audio insertion, paste cleanup, AI assistant integration, emoji picker, slash menu, mentions, import/export Word/PDF, form validation, and source code view in Angular applications.
飞书云盘增强命令组。分块上传大文件（>20MB 自动 3 段式）、流式下载、 文档异步导出（markdown 快捷路径 / sheet+bitable csv / sub-id / 有界轮询 + resume）、 文档异步导入、文件/文件夹移动（folder 自动轮询）、富文本评论（text/mention_user/link + wiki URL 解析 + 局部评论）、通用异步任务查询。 当用户请求"上传大文件"、"下载云盘文件"、"导出为 pdf/markdown/xlsx"、"导入 docx 到云文档"、"移动文件夹"、"添加文档评论"、"@某人评论文档"、"从 wiki 链接评论"、 "查询异步任务状态"、"drive 任务 resume"、"分块上传"、"feishu drive"、"lark drive"时使用。 本 skill 与老的 file/media/comment 命令组并存，提供更强能力（User Token 支持、 异步 resume、富文本评论），基础场景仍可用 file/media。
Export Feishu documents or knowledge base documents to Markdown files, or export them to formats such as PDF/Word/Excel (asynchronous tasks). It also supports importing local DOCX/XLSX files into Feishu cloud documents. It is triggered when users request "export document", "convert to Markdown", "save as md", "export PDF", "export Word", "convert docx to Feishu", "import docx". Markdown is stored in the /tmp directory as an intermediate format.