Automate scholarly paper discovery and ingestion into a Neo4j knowledge graph.
npx skills add https://github.com/YH-05/quants --skill kg-enrich-auto
Please help me install this Agent Skill. Skill: kg-enrich-auto Source: https://github.com/YH-05/quants/tree/main/.claude/skills/kg-enrich-auto Command: npx skills add https://github.com/YH-05/quants --skill kg-enrich-auto
Automatically searches for academic papers using alphaxiv MCP and continuously ingests results into a Neo4j knowledge graph, enabling ongoing knowledge accumulation until a specified END_TIME.
Run kg-enrich-auto with END_TIME set to a future ISO 8601 timestamp to start the continuous enrichment cycle.
High-intent search queries and answers about installing and using this skill.
Automatically ingest academic papers into a Neo4j knowledge graph by running an autonomous loop that uses alphaxiv MCP for discovery, creating Source, Author, Topic, and Claim nodes with deterministic MERGE-based Cypher patterns for idempotent writes.
Continuous knowledge graph enrichment runs until a specified time limit by setting the END_TIME parameter to a future ISO 8601 timestamp, driving a cyclic process of gap analysis, search, ingestion, connectivity, and optimization.
Structure scholarly literature review data by ingesting paper metadata into Neo4j as Source nodes and creating relationships like AUTHORED_BY, TAGGED, MAKES_CLAIM, and USES_METHOD to map complex academic connections for meta-analyses.
Gap analysis is fully automated within the cyclic process, requiring no manual intervention between searches. The workflow autonomously identifies missing knowledge, searches via alphaxiv MCP, ingests results, and optimizes graph connectivity continuously.
Neo4j MERGE-based Cypher patterns ensure deterministic, idempotent writes by generating specific IDs and using MERGE clauses to prevent duplicate nodes or relationships during the autonomous academic paper ingestion process.
Scholarly paper metadata extracted includes Source nodes representing papers, Authors, Topics, and Claims, connected through structured relationships to enable comprehensive research trend exploration and living knowledge accumulation.
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