Ingest, score, and promote raw knowledge sources into a structured entity graph.
npx skills add https://github.com/broomva/skills --skill bookkeeping-broomva
Please help me install this Agent Skill. Skill: bookkeeping Source: https://github.com/broomva/skills/tree/main/skills/knowledge/bookkeeping Command: npx skills add https://github.com/broomva/skills --skill bookkeeping-broomva
This skill solves the problem of fragmented, lost, or unindexed knowledge by providing a robust, automated pipeline to capture, score, and organize information into a permanent entity graph.
Run the bookkeeping pipeline to ingest, score, and promote all pending knowledge items in the current workspace.
High-intent search queries and answers about installing and using this skill.
Automating knowledge ingestion into an entity graph requires processing raw markdown records through a pipeline that scores content for novelty and promotes high-signal items into a queryable structure. This skill handles that workflow using PyYAML and mistune.
Distilling conversation transcripts into indexed entity pages involves parsing raw notes, scoring them for relevance, and deduplicating concepts to build an interconnected knowledge base. This skill automates that synthesis to ensure insights are immediately queryable.
Yes, processing markdown-based knowledge records and validating schema compliance within this pipeline requires both PyYAML and mistune dependencies to parse and structure the raw input sources correctly.
Entity resolution in a knowledge graph works by automatically deduplicating concepts and flagging clusters of related entities for synthesis. This ensures the knowledge base remains clean and interconnected after ingesting unstructured research notes.
Yes, this knowledge engine applies directly to research workflows and long-term memory management for AI agents by capturing fragmented information and organizing it into a permanent, queryable entity graph.
Markdown-based knowledge records require strict schema compliance for successful entity graph generation. Sources failing validation or lacking structured metadata may not score high enough for promotion to the final queryable knowledge base.
H2OSLabsImport YAML-frontmatter Markdown files from .synnovator into SQLite via SQLAlchemy models.
u9401066Extract concepts, entities, and relationships from educational materials into structured JSON knowledge graphs.
vuanhtu1993Create, validate, and package Claude Skills into .skill files.
neo4j-contribIngest PDFs and text into Neo4j knowledge graphs via SimpleKGPipeline.
