How might graphify's knowledge graph help detect gaps and duplication to improve the graph

[dharmeshgordhan]

This is super cool thanks for publishing. I have some psuedo-unstructured thoughts I wanted to share and propose as an idea.

What do you think about a feature in graphify that adds a new query mode that instead of asking: "what does the graph know about x", we ask: "what should be known about x, and how much does the corpus already cover". The motivation is in using the knowledge graph to audit docs and knowledge bases to improve them and inform what to write or refine next. This could also be extended to report on "where our content duplicates information".

I see the spirit of graphify is a tool to understand and represent existing content in an accessible way - not in content generation. This is primarily a gap analysis and coverage mapping idea. So I'm weary on if this is best as a complimentary tool or a feature in graphify.

Potential commands

/graphify plan content-plan.md     # ingest a content plan, merge into graph
/graphify plan content-plan.md --gaps     # ingest and immediately run gap report
/graphify plan --dups                             # duplicate report against existing plan nodes
/graphify plan content-plan.md --export-gaps gaps.md    # write gap report to file
/graphify plan content-plan.md --export-dups dups.md    # write duplicate report to file
/graphify add --stub-wiki gaps.md        # ingest a gaps report to create placeholder articles. 

A potential workflow might be:

1. Someone / thing generates an outline given a topic: (topic -> pages -> page sections -> sub sections). The outline could be expanded to include other metadata like audiences.
2. This is ingested as a first-class corpus artefact with nodes and relationships.
3. Gap detection graph queries - plan nodes with no high confidence EXTRACTED edges to the corpus, or a low count of INFERRED edges.
4. Write out potential gaps that can be responded to.
5. Duplicate detection graph queries - plan nodes with multiple corpus references, multiple inferred relationships.

A potential report:

## Gap report: content-plan.md
[topic] Brushing Your Teeth
  [page] Technique                      ✅  11 corpus nodes, 9 EXTRACTED edges
    [section] Angle of the brush        ✅  7 nodes
    [section] Circular vs back-and-forth ⚠️  3 nodes, 2 INFERRED (conf: 0.61)
    [section] How long to brush         ✅  6 nodes, 5 EXTRACTED edges
  [page] Equipment                      ⚠️  mixed confidence
    [section] Manual vs electric        ✅  8 nodes, 6 EXTRACTED edges
    [section] Toothbrush hardness       ⚠️  3 nodes, INFERRED only (conf: 0.55)
    [section] When to replace your brush ❌  No corpus coverage
  [page] Toothpaste                     ⚠️  partial
    [section] Fluoride                  ✅  9 nodes, 7 EXTRACTED edges
    [section] Whitening vs sensitive    ⚠️  4 nodes, 2 INFERRED (conf: 0.60)
    [section] Children's toothpaste     ❌  No corpus coverage
  [page] Common Mistakes                ❌  No corpus coverage
    [section] Brushing too hard         ❌  No corpus coverage
    [section] Rinsing immediately after ❌  No corpus coverage

4 gaps identified.

Hint: Run `graphify add --stub-wiki <path-to-gaps.md>` to create placeholders for missing articles.

## Duplicate report: content-plan.md
[section] When to replace your brush    ⚠️  2 corpus nodes — CONFLICT DETECTED
    source: dentist-guide.pdf
    source: manufacturer-faq.md

[section] How long to brush             ⚠️  DUPLICATION — 4 corpus nodes

I think the content plan itself could be a graph rather than a simpler flat hierarchical structure but thought I'd start there.