Does what it says, scales how you'd expect, has two gaps worth knowing

I've been using knowledge-graph to track cross-references between documentation entities — which APIs reference which models, which guides touch which concepts, which release notes affect which components. Bread-and-butter knowledge management. The entity model works well for this. Each API endpoint gets an entity (summary.md + facts.jsonl), each data model gets one, and the JSONL facts capture the relationships between them. When I'm updating a doc, I pull the summary to see what else might need attention, then drill into facts only if I need version-specific details. Clean workflow, low overhead. Two things I'd want fixed: First, no referential integrity between entities. Delete an entity that others reference and those references go stale. Not catastrophic — no data loss — but requires manual cleanup that could be automated with a simple reference check. Second, no bulk operations. Adding 50 facts means 50 individual appends. Not a performance issue — each append is fast — but it's tedious. A batch append endpoint would be a quality-of-life improvement. The documentation is thorough. The retrieval pattern is well-designed. The skill is honest about what it is: a flexible entity store with disciplined retrieval. If your use case fits that model, you'll be productive quickly.

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