Follows the Microsoft Learn learn-pr convention exactly (see documentation standard). The engine is ours, built from scratch (yuva/Rust serve + namzu/TS build); the format is the standard (portability + certification fit).
learn/
├─ achievements.yml # ### YamlMime:Achievements (badge/trophy)
├─ docs.config.json # build config (docfx.json analog)
├─ <product>/ # e.g. cogitave/, yuva/, namzu/
│ ├─ <module-slug>/
│ │ ├─ index.yml # ### YamlMime:Module
│ │ ├─ 1-<unit>.yml … N-<unit>.yml # ### YamlMime:ModuleUnit
│ │ └─ includes/<N>-<unit>.md # each unit's prose (separate)
│ └─ <path-slug>/index.yml # ### YamlMime:LearningPath
└─ docs/ # engine spec + authoring guide (Diátaxis, front matter)
- Linked by UID xref, no physical nesting:
Module.units[]= ModuleUnit UIDs;LearningPath.modules[]= Module UIDs. - Prose always lives in a separate
.mdunderincludes/(never embedded in the unit yml). - Knowledge-check = structural YAML (
quiz→ questions → choices{isCorrect, explanation}). - Achievement uid: badge →
….badge, trophy →….trophy. - Metadata: ISO-8601 dates (we improve on Learn's MM/DD/YYYY).
UIDs are immutable and decoupled from the physical path. Reserve a stable namespace per training type so the UID graph stays unambiguous:
| Type | UID shape | Achievement |
|---|---|---|
| Learning path | cogitave.learn.paths.<path-slug> |
trophy → cogitave.learn.paths.<path-slug>.trophy |
| Module | cogitave.learn.<module-slug> |
badge → cogitave.learn.<module-slug>.badge |
| Unit | cogitave.learn.<module-slug>.<unit-slug> |
— |
The cogitave.learn.paths.* namespace is reserved for learning paths; never give a module a paths. UID. Code snippets are not UID nodes — see the snippet registry.
cogitave/agent-platform-fundamentals/—### YamlMime:LearningPath, uidcogitave.learn.paths.agent-platform-fundamentals, trophycogitave.learn.paths.agent-platform-fundamentals.trophy. Sequences the two modules below.
cogitave/get-started-with-yuva/— the Yuva agent operating system (run your first agent). Badge….get-started-with-yuva.badge.cogitave/build-your-first-agent-with-namzu/— build an MCP-native agent with the Namzu kernel (intro → what-is-namzu → exercise → knowledge-check → summary). Badge….build-your-first-agent-with-namzu.badge.
docs/engine-architecture.md— the from-scratch engine spec: ACQUIRE→PARSE→ENRICH→INDEX→EMIT→PUBLISH, content-addressed incremental builds, monodocs aggregation, schema-DSL, native MCP, edge-first search.docs/authoring-guide.md— how authors write content: the extension set (alerts, includes,:::code, tabs,:::image, zone pivots, monikers, xref), metadata, Diátaxis mapping.
docs.config.json— content roots, metadata defaults, moniker registry, validation rules (schema + broken-xref/link = blocking), output targets (HTML + JSON content API + MCP +llms.txt).
The full knowledge platform (build/serve/index/MCP) is task #15. This folder is the content source + the engine/authoring spec + a proof of the convention.