post-indexing-analysis

What problem does it solve?

It automates post-run diagnostics for indexing and graph-building workflows, helping you quickly understand whether a run completed correctly, drifted in quality, or produced broken graph and vector data.

Core Features & Use Cases

• Indexing Run Review: Summarize the latest indexing execution, including stages, timing, run-end status, and collection state.
• Vector Quality Checks: Detect dimension mismatches, norm drift, zero vectors, and self-recall problems in Qdrant collections.
• Graph Integrity Analysis: Inspect SQLite call graphs, Neo4j structures, and graph_embeddings for orphan nodes, dangling calls, and relationship imbalances.
• Use Case: After a long ingestion job, use this Skill to generate a report that explains whether the collection is healthy, whether the graph is consistent, and where anomalies need attention.

Quick Start

Ask the skill to analyze the latest indexing run and produce a report for the relevant collection or graph source.