The Documentation Intelligence Layer for AI Coding Agents - provides MCP tools for documentation search, API discovery, code examples, verification, and context generation
Analyze impact of documentation changes on project workspace files
Verify agent code against indexed API schemas and detect mismatches, deprecations, or missing parameters
Compare documentation versions and snapshots to detect added, removed, or deprecated APIs
Deterministically export agent guidance files in multiple formats (AGENTS.md, CLAUDE.md, skill.md, llms.txt, docs-map.md)
Search and inspect structured API endpoints from OpenAPI/Swagger specifications
Search and filter first-class code examples by language, framework, or task
Search explicit warnings, deprecations, breaking changes, and runtime restrictions in documentation
Deterministically compile evidence-grounded implementation recipes from indexed documentation
Retrieve full documentation content for a specific page by ID or URL
Export a structured documentation map with hierarchical organization of all indexed content
Pack relevant documentation context optimized for AI coding agent implementation tasks
Retrieve version information and changelog for indexed documentation sources
Discover, fetch, normalize, and ingest documentation from a URL into the indexed repository
List all indexed documentation sources with version status and snapshots
Search indexed documentation chunks by query with hybrid full-text and semantic matching
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 0 | 2026-07-28+ | v2 |