npx skillsauth add liza-mas/liza testingInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Tests are the immune system — they reject bugs, not document them.
| Code | Test | Interpretation | |------|------|----------------| | Working | Green | Good | | Buggy | Red | Good (bug exposed) | | Working | Red | Wrong expectations | | Buggy | Green | DANGEROUS | | Unknown | Red | STOP — use Analysis Framework below |
ANTI-PATTERN: The most dangerous instinct is to "fix" failing tests by accepting whatever source currently does.
Ask for context:
Default heuristic: Tests encode intent; assume the test is correct until evidence suggests otherwise. Source drifts; tests usually don't drift without reason.
Analysis Framework:
FORBIDDEN without approval:
Allowed: Fresh repro tests capturing current failure (existing tests untouched).
Quality Standards:
pytest.raises(ValueError, match="...")Assertion Strength: Would this assertion pass for a broken implementation? If yes (tautology, type-only, existence-only, shape-only), strengthen it.
Mocking Discipline: Test the code, not the scaffolding. Heavy mock setup suggests you're testing assumptions about dependencies, not behavior. Mock external boundaries (APIs, DBs, filesystems), not internal logic.
Paired Coverage: For each positive test, consider a negative counterpart. Happy-path-only is a red flag for complex source.
Coverage Relevance: "Tests pass" ≠ "tests exercise changed code". For non-trivial changes, verify tests cover modified paths.
Signal Hierarchy: Integration failures > Unit failures for architectural changes. Green units with red integration = units work but don't compose.
Structure: Prefer GIVEN / WHEN / THEN blocks for readability. Omit a section when empty; the structure clarifies intent, not ceremony.
Template Principle: Identify one high-quality test file as reference. Match its patterns.
Flaky Tests: Flakiness is a bug, not noise. When encountered: isolate, report, do not retry-until-green. Flakiness masks real failures.
development
Coordinate Pairing-mode doer/reviewer sessions through a Markdown blackboard. Use when the user invokes /adversarial-pairing with role and blackboard-path arguments or asks multiple pairing agents to coordinate plan review, implementation, staged code review, and follow-up review rounds without Liza multi-agent mode.
data-ai
Analyze Liza agents logs
development
Code Review Protocol
tools
Analyze Liza `.liza/agent-prompts/` and `.liza/agent-outputs/` from a context-engineering perspective: prompt payload shape, context budget use, cacheability, duplicated or missing context, instruction hierarchy, tool-output pressure, role-specific context fit, and prompt-output feedback loops. Use when diagnosing agent context bloat, prompt drift, poor agent handoffs, repeated misunderstandings, excessive tool output, or whether Liza agents received the right information at the right time.