{"slug": "schemacrawler-scribe-google-okf-ai-ready-database-docs-you-can-keep-in-git", "title": "SchemaCrawler Scribe + Google OKF: AI-Ready Database Docs You Can Keep in Git", "summary": "SchemaCrawler Scribe generates structured database documentation from live schema metadata using Google Open Knowledge Format (OKF), producing artifacts that work for both developers and AI agents. The tool outputs OKF Markdown files that are easy to review in Git and consume with AI tooling, turning documentation into part of the engineering workflow. It supports command-line and Docker usage, with options for titles, expanded output, and schema lint reports.", "body_md": "If your database documentation is always behind production, this is for you.\n\n**SchemaCrawler Scribe** generates structured database documentation directly from live schema metadata, using ** Google Open Knowledge Format (OKF)**.\n\nThe result is documentation that works for both developers and AI agents, without creating a second documentation workflow.\n\nSource code: [SchemaCrawler/schemacrawler-scribe](https://github.com/schemacrawler/SchemaCrawler/tree/main/schemacrawler-scribe)\n\nMost teams end up in one of two modes:\n\nSchemaCrawler Scribe targets the middle ground:\n\nThis turns documentation into part of your engineering workflow, not a side task.\n\nSchemaCrawler Scribe outputs in [Google Open Knowledge Format (OKF)](https://github.com/GoogleCloudPlatform/knowledge-catalog/blob/d44368c15e38e7c92481c5992e4f9b5b421a801d/okf/SPEC.md), which gives you one format that serves multiple use cases:\n\nIn short: one documentation artifact that supports people, automation, and long-term maintainability.\n\nSchemaCrawler Scribe is in the same family of tooling as SchemaSpy: both crawl schema metadata and generate browsable documentation.\n\nLike SchemaSpy-style documentation workflows, Scribe covers:\n\nSo if your team already likes auto-generated schema docs and relationship views, SchemaCrawler Scribe keeps that experience while producing **Google OKF Markdown** artifacts that are easier to review in Git and consume with AI tooling.\n\nRun standard SchemaCrawler from the command line or Docker. Use the `scribe`\n\ncommand with `okf`\n\noutput format.\n\nTips:\n\n`--title`\n\nto label the generated documentation set`--expanded-output`\n\nto generate a directory tree instead`--include-lint`\n\nto generate schema design issue reports\n\n```\ndocker run \\\n  --mount type=bind,source=\"$(pwd)\",target=/home/schcrwlr/share \\\n  --rm -it \\\n  schemacrawler/schemacrawler \\\n  /opt/schemacrawler/bin/schemacrawler.sh \\\n  --server=sqlite \\\n  --database=sc.db \\\n  --info-level=maximum \\\n  --command scribe \\\n  --output-format okf \\\n  --title \"Books Database\" \\\n  --expanded-output \\\n  --include-lint \\\n  --load-row-counts \\\n  --output-file=share/schema\n```\n\nIf you are using PowerShell, replace each trailing backslash with a backtick for line continuation.", "url": "https://wpnews.pro/news/schemacrawler-scribe-google-okf-ai-ready-database-docs-you-can-keep-in-git", "canonical_source": "https://dev.to/sualeh/schemacrawler-scribe-google-okf-ai-ready-database-docs-you-can-keep-in-git-2off", "published_at": "2026-07-14 23:58:09+00:00", "updated_at": "2026-07-15 00:27:11.715982+00:00", "lang": "en", "topics": ["developer-tools", "artificial-intelligence", "large-language-models"], "entities": ["SchemaCrawler", "Google Open Knowledge Format", "SchemaSpy", "Docker"], "alternates": {"html": "https://wpnews.pro/news/schemacrawler-scribe-google-okf-ai-ready-database-docs-you-can-keep-in-git", "markdown": "https://wpnews.pro/news/schemacrawler-scribe-google-okf-ai-ready-database-docs-you-can-keep-in-git.md", "text": "https://wpnews.pro/news/schemacrawler-scribe-google-okf-ai-ready-database-docs-you-can-keep-in-git.txt", "jsonld": "https://wpnews.pro/news/schemacrawler-scribe-google-okf-ai-ready-database-docs-you-can-keep-in-git.jsonld"}}