Scan Results: https://docs.baseten.co/overview

Vanity URL: scan.glintbase.xyz/baseten-scan

54/100
Agent Readiness Score

AI-Friendly Docs

Parseable by AI models but has high token usage or lacks standard machine-readable hooks.

Category Breakdown

Context Optimization21 / 30
Code Block Execution23 / 30
Machine Readability0 / 20
Agent Tooling & MCP10 / 20

Detailed Findings

Context Optimization

21/30

llms.txt Auto-Discovery

llms-full.txt Consolidated Docs

Markdown Content Negotiation (Accept: text/markdown)

DOM Cleanliness Ratio (1% markdown/HTML)

↳ AI Agent Fix Prompt
Reduce layout boilerplate (header, footers, scripts) or use Markdown Content Negotiation to strip DOM noise.
🔧

Code Block Execution

23/30

Terminal Prompt Pollution (No "$" prefixes in copyable code)

Dependency & Import Completeness

↳ AI Agent Fix Prompt
Review every code example in my documentation.
For each snippet, ensure it is fully self-contained and executable.

Every code block must include:
1. All import / require statements at the top
2. Package installation command in a comment
3. Authentication initialization if the code makes API calls
4. All variables defined before use — no undefined references
5. Inline comments explaining WHY each step is done, not just what

An AI agent copying this snippet must be able to run it
without searching for any additional information.

Details: The snippet lacks explicit installation commands or package imports. Configuration details for dependencies like TRT LLM or Hugging Face model loading are implied but not provided.

Dynamic Variable Placeholders

🔍

Machine Readability

0/20

OpenAPI/Swagger Spec Auto-Discovery

↳ AI Agent Fix Prompt
Expose an OpenAPI or Swagger specification at a standard path (e.g. /openapi.json) or link to it using the "Link" HTTP response header with rel="openapi".

JSON-LD Structured Schema (TechArticle / APIReference / Guide)

↳ AI Agent Fix Prompt
Embed a <script type="application/ld+json"> block classifying your docs as a TechArticle, Guide, or APIReference, containing semantically enriched metadata.
🤖

Agent Tooling & MCP

10/20

Model Context Protocol (MCP) Server Integration

Error Code Diagnostics & Cross-Referencing Index

↳ AI Agent Fix Prompt
Provide a comprehensive table or section listing error codes, their causes, and solutions. This lets agents cross-reference error stacks and resolve integration errors automatically.