lab: code-miner / repo context / LLM handoff
Context: LLMs help with code when they receive the right context. But a large project cannot be placed into a prompt as-is: too much noise and too little structure.
Problem: string search finds matches, but it does not explain the system. For a task, it is more important to understand entrypoints, ownership boundaries, related models, migrations, side effects and tests that protect behavior.
Approach: code-miner should build a map: routes, controllers, models, views, assets, commands, config and recent related changes. The output should be a compact context pack that can be handed to an LLM or a human.
Conclusion: AI assistance in development often depends less on the model and more on context packaging. A good pack reduces hallucinations and speeds up review.
Next step: add file ranking by task proximity and an automatic list of questions when context is insufficient.