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Google's Open Knowledge Format (OKF) v0.1 — an open, vendor-neutral spec for representing knowledge as markdown files with YAML frontmatter, designed for AI agent consumption. - SKILL.md: core instructions, frontmatter spec, conformance criteria, cross-linking rules, relationship to other formats, quick start - references/spec-summary.md: full OKF v0.1 specification reference - references/bundle-architecture.md: directory structure and conventions - references/use-cases.md: real-world adoption and patterns - scripts/okf-bundle-validate.py: validate OKF bundle structure - assets/concept-template.md: template for creating concept files - assets/example-bundle/: minimal conformant OKF bundle
39 lines
1.2 KiB
Markdown
39 lines
1.2 KiB
Markdown
---
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type: <Type name> # REQUIRED — e.g. "BigQuery Table", "Metric", "Playbook", "API Endpoint"
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title: <Human-readable display name> # Recommended
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description: <One-line summary> # Recommended — used in index.md entries and search snippets
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resource: <Canonical URI> # Optional — URL for the underlying asset
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tags: [<tag1>, <tag2>] # Optional — cross-cutting categorization
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timestamp: <YYYY-MM-DDThh:mm:ssZ> # Optional — ISO 8601 last-modified time
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---
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# Concept Title
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A short paragraph explaining what this concept is and why it matters. What problem does it solve? When would someone reach for this?
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## Schema
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If this concept describes a structured asset (table, API, dataset), document its fields here.
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| Field | Type | Description |
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|-------|------|-------------|
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| `field_name` | TYPE | Description of the field |
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| `foreign_key` | TYPE | FK to [related concept](/path/to/concept.md) |
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## Examples
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Usage examples as code blocks or scenarios.
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```sql
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SELECT field_name FROM table WHERE condition;
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```
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## References
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* [Related concept 1](/path/to/concept-1.md)
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* [Related concept 2](/path/to/concept-2.md)
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## Citations
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[1] [External source](https://example.com)
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