LLM Narrative Engine Series: How Integration Tests Freeze Parser Behavior

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A developer building an LLM-based narrative engine has detailed how integration testing is used to lock in stable parser behavior across code changes. The approach uses 'golden files' — saved JSON snapshots of expected parse results — which are automatically compared against new outputs after every code modification. If a change is intentional, developers can refresh the golden file using a simple command-line flag, preventing accidental regressions. The hand-written parser also enforces semantic validation at parse time, rejecting incomplete data such as empty character names or missing rule fields before a struct is ever created. Additionally, the engine includes a history-truncation mechanism, verified by integration tests, that caps conversation history to a fixed number of recent turns to prevent unbounded memory growth.

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