Guide validation and error handling toward system boundaries, where external data enters the application. Keep business rules in functions independent of frameworks, use validated types internally, and avoid repeating checks throughout the code.
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Apply when wiring validation, error handling, or framework adapters. Concentrate guards at system boundaries (CLI, config, network, external APIs); trust internal types and keep business logic in pure functions.
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Place validation, type narrowing, and error handling at system boundaries. Trust internal code unconditionally. Business logic lives in pure functions. The shell is thin and mechanical.
Why: Scattered validation is noisy, redundant, and gives a false sense of safety. Keep logic out of framework wiring so it can be tested without the framework.
The pattern:
Applications:
Validation and error handling:
Code organization:
The tests:
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Plan types, function inputs and outputs, and module boundaries before implementation. Compare structurally different designs from multiple AI models, document the chosen approach, and guide coding while tracking changes to the agreed design.
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Generate several candidate solutions in parallel, compare them against concrete criteria, and choose a base. Combine useful parts from other candidates, then verify the final artifact and document why each major choice was made.
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Turn recurring work habits and communication preferences into a personal agent skill. It combines evidence from workspace conversations with direct questions, then drafts or updates instructions for how agents should work with you.
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Monitor an open pull request, fix failing automated checks and merge conflicts, and address straightforward review feedback. Recheck after updates, report the resulting status, and hand decisions requiring design judgment back to the user.
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Checks whether performance measurements support a speedup, slowdown, or technology choice. It examines bottlenecks, production settings, errors, repeatability, and completed work, then guides reporting with run counts, ranges, and a clear verdict.
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Investigate what a code change could break beyond the edited files. Trace downstream effects, identify the key assumption behind its safety, and test that assumption with real code while clearly reporting unresolved risks.
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