Test Coverage

Write valuable tests that improve confidence and coverage; prefer behavior likely to regress over assertions that only inflate percentages.

Quick Start

1. Explore the repo and run scripts/repo_test_probe.py from the skill directory to infer stack, tooling, and coverage artifacts.
2. Use coverage reports for cold spots, or infer gaps from changed code, complex logic, public APIs, and error-handling branches.
3. Match the project's existing style, fixtures, and naming; run the narrowest test command first, then broaden until coverage improves.

Pick High-Value Targets

• Prioritize: branchy business logic, error handling/retries/validation, serialization/parsing/adapters, bug-prone changes, public entry points.
• De-prioritize: thin wrappers, snapshot-heavy/implementation-coupled tests (unless already relied on), mock-only assertions with no observable outcome.

Guardrails