lintlang

Overview

Static analysis for AI agent configs, tool descriptions, and system prompts. It catches vague tool descriptions, missing stop conditions, and schema gaps before runtime using zero-LLM deterministic checks. Built for CI pipelines.

Best for

Best for
Teams building AI agents who want CI-time config validation without LLM overhead

Use cases

• Lint agent configs in CI pipelines
• Validate tool description clarity and schema completeness
• Detect missing stop conditions before deployment

Notes

Static analysis for AI agent configs, tool descriptions, and system prompts. It catches vague tool descriptions, missing stop conditions, and schema gaps before runtime using zero-LLM deterministic checks. Built for CI pipelines.

137 stars on GitHub. Last updated 2026-10-03. Licensed Apache-2.0.

Use cases

• Lint agent configs in CI pipelines
• Validate tool description clarity and schema completeness
• Detect missing stop conditions before deployment

Pros

• Deterministic checks with no LLM runtime dependency
• Catches config issues before they reach production
• Open source community project in Python

Cons

• Static analysis cannot catch runtime behavior issues
• Limited to patterns detectable without language understanding
• Small community with 137 stars, so maturity is limited

Indexed from awesome-llmops and enriched against its public facts.