agent-architecture-analysis

To audit agent code against 12-Factor principles, run an analysis on your Python codebase using search patterns and file heuristics to evaluate compliance levels for each of the 13 architectural factors.

12-Factor Agents compliance analysis evaluates an LLM agent codebase to determine adherence to best practices for prompt ownership, context window management, tool structure, execution state unification, and control flow ownership.

Check LLM agent architecture production-readiness by evaluating natural language to tool call handling, error management, statelessness, and human contact capabilities to identify architectural anti-patterns before deployment.

This architecture audit specifically analyzes Python codebases using provided search patterns and file heuristics, meaning it is not designed for non-Python LLM systems without adaptation.

A 12-Factor Agents methodology review evaluates 13 factors including natural language to tool calls, prompt ownership, context window management, launch/pause/resume capabilities, trigger flexibility, and context pre-fetching.

An agent architecture review identifies weak context window management by analyzing how your codebase handles execution state unification and context pre-fetching, exposing anti-patterns in statelessness and focus.