Agent-Ready
Documentation
Infrastructure.
Glintbase automatically creates, maintains, validates, deploys, and optimizes documentation for both human developers and autonomous AI agents. Start with code. End with trusted intelligence.
Start with Code. End with Documentation.
AST-driven parsing translates typescript signatures, endpoints, and file dependencies into production-grade Markdown and MDX documents instantly.
The Core Problem
Your product is not ready for AI agents
Traditional static documentation is built for manual browser reading. It fails in the developer ecosystem of autonomous agents because of four fundamental blind spots:
Documentation Drift
API signatures change daily, but docs update monthly. Stale documentation results in prompt errors, broken integrations, and code translation failure.
Broken Code Examples
Markdown example blocks are rarely run in production. Outdated parameters cause AI assistants to write broken boilerplates that compile with errors.
Zero Machine Structure
Agents cannot parse raw, infinite HTML folders efficiently. Without semantic structures like llms.txt, assistants waste tokens and context window.
Invisible To Ecosystems
New systems search semantic spaces, not Google. If your API lacks agent-ready configurations (MCP schema), LLMs will hallucinate or overlook it.
Test your documentation's AI compatibility instantly
How easily can coding systems like **Cursor, Claude Code, and Copilot** query, parse, and write code against your product? Enter your docs URL to receive an instant compatibility audit.
Get a composite score (0-100) across 5 criteria bands.
Identify missing llms.txt, high token bloat, and invalid syntax.
Acquire immediate prompt templates to fix and patch failures.
Developer Discovery
The New Discovery Paradigm
Developers increasingly learn products, libraries, and web APIs directly inside workspace environments through tools like **Cursor**, **Claude Code**, and **GitHub Copilot**.
If coding agents can effortlessly read and parse your product's API framework, your repository integrations and API usage will grow rapidly.
Scanning docs/auth... file not found. Falling back to Google search. Stalling... Auth API parameter mismatch.
Reading /llms.txt... Found match: authenticate(req). Exposes schema parameter definition. Initiating verify.
The Glint Engine
The Self-Healing Documentation Pipeline
How the platform automatically synchronizes codebase logic with both humans and machine clients in real time.
Glintbase connects to GitHub / Gitlab
Extracts AST patterns & creates docs structure
Detects codebase drift in real-time
Runs snippets in isolated test sandboxes
Deploys fast web portal hosted at edge
Exposes llms.txt & MCP server integrations
Platform Capabilities
The Five Pillars of Documentation Intelligence
Start with Code. End with Documentation.
No documentation? No problem. Glintbase maps code hierarchies, AST parameters, and dependencies automatically. It translates raw developer codebases into detailed manuals, guides, API layouts, and readmes out of the box.
Continuous Sync
Glintbase tracks codebase modifications, compares AST delta trees against existing files, drafts PR modifications, and triggers warning flags when drift is detected.
Sandbox Testing
Verify code snippets written inside document headers. Automatically launch isolated sandbox node systems, run testing calls, check return layouts, and flag issues.
DocOps Infrastructure
Build and compile optimized static pages with layout components. Deploy direct documentation portfolios globally at the Edge, managing hosting pipelines automatically.
Agent Infrastructure
Bridge the human-machine documentation divide. Autogenerate machine-readable config descriptors, structured semantic indexes, and tool discovery assets.
Engine Output
Ecosystem Integration Outputs
Glintbase generates optimized configuration assets directly in the root of your application, enabling instant developer integration by coding agents.
# Glintbase Core API
## System Endpoints
- POST /v1/scan : Initiate AST evaluation
- GET /v1/drift : Retrieve divergence statistics
## Schema Definitions
- Request: { repo_url: string, commit_sha: string }
- Response: { status: 'diverged' | 'aligned', score: number }
## Authentication
Authorization: Bearer <publishable_key>Reserve Node
Initialize entry into the synchronization protocol.