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Is Your Library
Agent-Ready?

One-click audit reveals how coding agents really treat your code.

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See StackBench in Action

Why StackBench?

Most documentation fails when agents try to use it. Here's how we fix
that.

The Old Way



Hope and Pray

Write docs, ship code, hope agents understand it



Manual Testing

Manually test with ChatGPT, get inconsistent results



Late Discovery

Find out in production that agents can't use your API

The StackBench Way



Automated Analysis

Real agents test your code across multiple scenarios



Actionable Reports

Get specific fixes ranked by impact on agent success



Continuous Monitoring (coming soon)

Track agent-readiness over time as your code evolves

How StackBench Works

StackBench simulates how coding agents actually use your library
documentation. We extract real use cases, then test if agents can
implement them successfully.

Phase 1

Extract Use Cases

We analyze your documentation to find realistic scenarios that
developers would actually implement.

Smart Doc Scanning
Clone repo and scan .md/.mdx files for code examples
AI Analysis
Advanced AI extracts realistic use cases from documentation
Diversity Optimization
15 distinct cases across beginner to advanced complexity
Phase 2

Agent Testing

Coding agents attempt to implement each use case using only your
documentation as a guide.

Isolated Execution
Each use case runs in its own Docker container
Real Constraints
Read-only docs with realistic testing environment
Complete Tracing
Complete tracing logs for the analysis agent

What You Get

Detailed insights into how well your documentation works with coding
agents

Success Rate

See exactly which use cases agents can implement successfully

Failure Analysis

Understand why agents fail and what's missing from docs

Agent Traces

Full execution logs showing agent decision-making process

Built For

Whether you're building for millions or for your team, StackBench
helps you get ready for the AI-first future.

Library Maintainers

Ensure your open source project is ready for the AI Agents era

Higher adoption rates
Better developer experience
Reduced support burden

Platform Teams

Make your internal APIs agent-accessible across the organization

Faster team integration
Standardized documentation
Scalable onboarding

Product Engineers

Ship features that work seamlessly with AI coding assistants

AI-first development
Future-proof architecture
Enhanced productivity

Get Started

Join developers using StackBench to improve their documentation
quality through real implementation testing.

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