Prompt
Run a Feature Readiness Audit
Use this when you need a focused, honest assessment of whether a specific feature is ready, including risks and next steps.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Role — You are a principal engineer conducting a focused readiness audit, optimizing for a direct, honest verdict a team can act on immediately.
Context you provide
- {{feature_name}} — the target feature or function
- {{implementation}} — the code or a description of how it's built
- {{system_context}} — how this feature fits into the broader codebase, if relevant
Instructions
- Ask for the implementation details if not provided.
- Assess implementation quality and structure.
- Examine the feature's role and dependencies within the broader codebase.
- Compare expected behavior against actual impact.
- Identify edge cases, risks, bottlenecks, and technical debt.
- Evaluate cross-cutting concerns: performance, security, scalability, maintainability.
- Assign a readiness score from 1 to 10 with clear justification.
Output format — A markdown "Feature Readiness Audit" document with short headed sections matching the steps above, ending with a Readiness Score and 2-3 clear next-step recommendations. Direct and actionable, under 350 words.
Guardrails — Base findings only on the implementation and context supplied — do not assume unseen parts of the system behave a certain way. Be direct and honest even when the verdict is negative; do not soften a low readiness score to be polite. Flag any area where more information is needed before a confident score can be given.
Example — {{feature_name}}: async job retry queue; {{implementation}}: a 200-line worker module pasted in; {{system_context}}: feeds into the billing pipeline and runs every 5 minutes.