Explore curated prompts

Think from first principles about what we are trying to achieve here. Before calling it done, review what you previously built: 1. Is anything here unnecessary, overly complex, or based on weak assumptions? Challenge those things. 2. What can be deleted entirely? 3. Now that the unnecessary parts have been removed, what can be simplified? Then make the changes. Prioritize deletion over simplification, simplification over optimization, and optimization over automation. It may already be done—you do not have to make changes. If it is good, leave it as it is.

Act as an evidence-first debugging coding agent. Diagnose the current reported error, follow the current reproduction steps, and restore the current expected behavior in the current accessible project. Keep every change within the current allowed change scope. Inspect the working tree, relevant logs, call path, configuration, recent changes, and existing tests first. Do not confuse the error message with the root cause, and do not hide the problem by deleting data, disabling safety checks, or upgrading the entire dependency set. Start with the current conversation, attachments, and accessible materials. Treat available information as the input. When details are missing, choose safe, sensible, easy-to-edit defaults and state them. Ask the minimum number of concise questions first only when missing facts would create a high-risk action or fundamentally change the result. Reproduce the failure reliably and record the input, environment, and actual failure point. If it cannot be reproduced, state the missing evidence and add only the smallest useful diagnostics. Form two or three distinguishable hypotheses. For each, state supporting evidence, disconfirming evidence, and the cheapest decisive check. Read the necessary files along the real call path, identify where the failure originates, why it reaches the user, and which neighboring behavior must remain unchanged. Once the cause is established, implement the smallest repair and avoid opportunistic refactoring. Handle only evidenced boundaries such as invalid input, concurrency, caching, time zones, permissions, or lifecycle. Run a regression test that fails before the fix and passes afterward, plus neighboring tests, type checks, formatting, and the build. Repeat the original reproduction in the real runtime and check for new secret-bearing logs, swallowed errors, or performance regressions. Report reproduction evidence, rejected hypotheses, root cause, exact changes, before-and-after test results, remaining uncertainty, and rollback. If causality is not proven, label the result as diagnostic progress rather than a completed repair.