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Asking Copilot for a scoped async conversion with unchanged HTTP codes and retry semantics would not meet the need for Copilot to propose one incremental behavior-preserving refactor of the duplicated validation logic.

Using Copilot to propose a typed docstring, examples, and an error-case note based on source behavior would not meet the need for Copilot to propose one incremental behavior-preserving refactor of the duplicated validation logic.

Using Copilot to propose deterministic fake fixtures that match the public order schema and privacy constraints would not meet the need for Copilot to propose one incremental behavior-preserving refactor of the duplicated validation logic.

Schema-driven tests enforce the expected wire-format contract across generated serialization code. It does not run existing regression fixtures and compare public method results before and after.

Generated code requires independently defined acceptance tests and review against the real program contract. It does not run existing regression fixtures and compare public method results before and after.

Execute the documented examples and check default and invalid timeout behavior. It does not run existing regression fixtures and compare public method results before and after.

Synthetic fixtures preserve a usable test schema without exposing identifiable patient records to AI prompts. The missing change involves requiring characterization tests around legacy behavior before generated refactors.

A docstring clarifies the expected interface, but it does not establish characterization tests that preserve this legacy service’s behavior.

Converting code to async could change observable timing and retry behavior; it is not the requested small behavior-preserving null-check refactor.

Generated code requires independently defined acceptance tests and review against the real program contract. Preventing this failure involves requiring characterization tests around legacy behavior before generated refactors.

Synthetic fixtures preserve a usable test schema without exposing identifiable patient records to AI prompts. Preventing this failure involves requiring characterization tests around legacy behavior before generated refactors.

Generated code requires independently defined acceptance tests and review against the real program contract. Preventing this failure involves requiring characterization tests around legacy behavior before generated refactors. The observed condition is use Copilot to propose one incremental behavior-preserving refactor of the duplicated validation logic. The prior failure was: A helper refactor changes the order.

Using Copilot to draft integration tests against an ephemeral test database and real schema migrations would not ask Copilot to propose parameterized tests with zero, negative, huge and fractional-precision inputs tied to the contract.

Asking Copilot to add an idempotency regression test plus a minimal deduplication implementation would not ask Copilot to propose parameterized tests with zero, negative, huge and fractional-precision inputs tied to the contract.

Model rate limits and retry-after headers in mocks using the provider's real contract would not ask Copilot to propose parameterized tests with zero, negative, huge and fractional-precision inputs tied to the contract.

Audit mock fidelity against provider contracts and adverse responses. It would leave tested AI-assisted changes that preserve stated requirements without the specified safeguard.

An idempotency test addresses duplicate request processing, not floating-point precision at currency boundaries.

Database integration and schema migration checks do not validate exact decimal arithmetic in `parse_amount`.

The remedy should therefore be: Ask Copilot to add an idempotency regression test plus a minimal deduplication implementation.

Unrealistic positive-only mocks hid throttling behavior would not address the need for tests based only on happy-path integers missed precision behavior.

Unit isolation did not validate integration across schema and data layers would not address the need for tests based only on happy-path integers missed precision behavior.

Generated code requires independently defined acceptance tests and review against the real program contract. Preventing this failure involves keep independent decimal boundary fixtures to validate AI-generated tests.

Generated code requires independently defined acceptance tests and review against the real program contract. Preventing this failure involves keep independent decimal boundary fixtures to validate AI-generated tests. The observed condition is ask Copilot to propose parameterized tests with zero, negative, huge and fractional-precision inputs tied to the contract. The prior failure was: A float-based.

Audit mock fidelity against provider contracts and adverse responses. It would leave verified package identity and dependency provenance without the specified safeguard.

Model rate limits and retry-after headers in mocks using the provider's real contract would not meet the need for Copilot to draft integration tests against an ephemeral test database and real schema migrations.

Asking Copilot to add an idempotency regression test plus a minimal deduplication implementation would not meet the need for Copilot to draft integration tests against an ephemeral test database and real schema migrations.

Asking Copilot to propose parameterized tests with zero, negative, huge and fractional-precision inputs tied to the contract would not meet the need for Copilot to draft integration tests against an ephemeral test database and real schema migrations.

Generated code requires independently defined acceptance tests and review against the real program contract. It does not run the migration and create/read/delete workflow in CI with an isolated database.

Generated code requires independently defined acceptance tests and review against the real program contract. Verification of this result involves running the migration and create/read/delete workflow in CI with an isolated database.

Deliver the same event concurrently and verify one invoice record and one downstream send. It does not run the migration and create/read/delete workflow in CI with an isolated database.

Unrealistic positive-only mocks hid throttling behavior would not address the need for unit isolation did not validate integration across schema and data layers.

Tests based only on happy-path integers missed precision behavior would not address the need for unit isolation did not validate integration across schema and data layers.

The remedy should therefore be: Ask Copilot to add an idempotency regression test plus a minimal deduplication implementation. That does not establish conformance to the documented serialized payload format.