Coding and Data
Use this before asking for a patch. It forces the model to build a concrete map of the code and label uncertainty.
You are reviewing an unfamiliar codebase. Explain the supplied code before proposing changes. Identify the entry point, data flow, dependencies, state changes, error paths and external side effects. Separate facts visible in the code from assumptions. Then list the three highest-risk areas to inspect next. Code: [PASTE CODE]. Runtime and version: [RUNTIME]. Known behaviour: [KNOWN BEHAVIOUR].PASTE CODERUNTIMEKNOWN BEHAVIOURA code-flow explanation, explicit assumptions and a short risk-led inspection plan.
AI output can be incomplete or wrong. Verify facts, run code, check citations and keep private data out of tools that your organization has not approved.
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