Knowledge Catalog Documentation

Pages

1. OverviewKnowledge Catalog tooling surface: OKF bundles, kcmd Metadata as Code workspaces, enrichment and discovery agents, and the shortest paths to produce and publish metadata context.
2. InstallationPrerequisites, Python and Node.js setup, package installs, and credential configuration for BigQuery, Vertex AI or Gemini, and gcloud Application Default Credentials.
3. QuickstartFirst successful runs: initialize a kcmd workspace and pull metadata, produce an OKF bundle from BigQuery, or run the catalog enrichment agent and inspect output.
4. Open Knowledge FormatOKF v0.1 bundle structure, concept documents, frontmatter fields, index.md progressive disclosure, and cross-link semantics for vendor-neutral knowledge exchange.
5. Metadata as Codekcmd workspace model: catalog.yaml manifest, YAML and Markdown layouts, pull/push sync, reference layers, entry links, and glossary scope for Knowledge Catalog metadata.
6. Enrichment workflowsHow enrichment agents read source metadata, ground on external docs or code, emit OKF bundles or mdcode artifacts, and hand off to kcmd push for catalog publication.
7. Sync catalog metadataInitialize a kcmd workspace for BigQuery, knowledge base, entry group, BigLake, or glossary scope; pull snapshots; check status; and push local edits back to Knowledge Catalog.
8. Produce OKF bundlesRun the OKF enrichment agent against a BigQuery source with optional web crawl seeds, concept scoping, and two-pass BQ-then-web enrichment into a versionable bundle directory.
9. Run the catalog enrichment agentExecute table, doc, or context_overlay modes with Drive, local markdown, GitHub, feedback, glossary, and usage-signal inputs; refine output interactively before publishing.
10. Publish enriched metadataPush mdcode workspaces with kcmd, publish sample enrichment output via catalog APIs, and reconcile entry links and aspects without modifying read-only reference layers.
11. Visualize OKF bundlesGenerate self-contained viz.html graph viewers from OKF bundles with force-directed layouts, concept detail panels, backlinks, and in-browser markdown rendering.
12. Run the discovery agentDeploy the Knowledge Catalog discovery agent with ADK: required GCP APIs and IAM roles, environment variables, and root-agent or AgentTool integration patterns.
13. Evaluate enrichment outputScore enrichment runs with dynamic golden-free metrics or golden-based eval: structural validity, hallucination checks, fact recall, consistency across runs, and report artifacts.
14. kcmd CLI referencekcmd commands, init flags per source type, pull and push options including dry-run, force, validate-only, reference pull, and authentication via gcloud ADC.
15. catalog.yaml manifest referencescope, snapshot, publishing, reference, aliases, entry and aspect types, entryLinks reconciliation rules, and layout selection for YAML versus Markdown knowledge-base mode.
16. kcmd MCP server referenceMCP server startup, workspace path binding, and agent tools for pull, push, list-entries, lookup-entry, and modify-entry in agentic metadata workflows.
17. OKF enrichment-agent CLI referenceenrichment-agent enrich and visualize subcommands, BigQuery source flags, web crawl constraints, concept scoping, model selection, and environment variables.
18. Enrichment agent flags referenceagent_runner.py flags by mode: table, doc, context_overlay; source inputs, usage signal, glossaries, feedback, GitHub MCP, refinement, and required Vertex project and model values.
19. OKF bundle recipesCopy-paste enrichment recipes for GA4 merchandise store, Stack Overflow, and Bitcoin public datasets with seed files, exact commands, and expected bundle outputs.
20. Toolbox enrichment demoEnd-to-end TypeScript demo: kcmd init and pull, kcagent enrich with md-fileset MCP tools, fileset skills, prompt configuration, and BigQuery demo dataset setup.
21. TroubleshootingCommon auth, billing, push conflict, web crawl cap, glossary provisioning, and model credential failures with verification signals from tests and README constraints.
22. ContributingCLA requirements, fork-and-PR workflow, style expectations, and test commands for Python pytest and TypeScript npm run test across package directories.