ai-development-guide
Applies language-agnostic and backend technical decision criteria, anti-pattern detection, debugging, and quality gates. Use when reviewing general/backend…
Integration and E2E test design principles, ROI calculation, test skeleton specification, and review criteria. Use when designing integration tests, E2E tests, or reviewing test quality.
$ npx -y skills add shinpr/claude-code-workflows --skill integration-e2e-testing --agent claude-codeHow it fires
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Integration and E2E test design principles, ROI calculation, test skeleton specification, and review criteria. Use when designing integration tests, E2E tests, or reviewing test quality.
name: integration-e2e-testing description: Integration and E2E test design principles, ROI calculation, test skeleton specification, and review criteria. Use when designing integration tests, E2E tests, or reviewing test quality.
**E2E test design**: See [references/e2e-design.md](references/e2e-design.md) for UI Spec-driven E2E test candidate selection and browser test architecture. The reference uses Playwright as the default browser harness; substitute the project's standard when different.
| Test Type | Purpose | Scope | External Deps | Standard Budget per Input Design Doc | Implementation Timing | |-----------|---------|-------|---------------|-------------------|----------------------| | Integration | Verify component interactions in-process | Partial system integration (in-process modules; for UI components, the framework's in-process renderer e.g., RTL+MSW for React/TS) | Mocked or in-process | MAX 3 | Created alongside implementation | | fixture-e2e | Verify UI behavior in a browser with deterministic fixtures | Full UI flow with mocked backend / fixture-driven state | Mocked / fixture only — no live services | MAX 3 | Created alongside the UI feature | | service-integration-e2e | Verify critical user journeys against a running local stack | Full system across services | Live local services or stubs | MAX 1-2 | Earliest task where the proof boundary and required services are executable |
**Lane selection (E2E only)**:
One input Design Doc is one budget scope: apply each lane budget once across all ACs and candidates in that document. The two E2E lanes are budgeted independently — having a fixture-e2e for a journey does not consume the service-integration-e2e budget and vice versa. Treat the numbers above as enforced standard budgets. Exceed a budget only when an accepted requirement or a distinct failure mode cannot be proved by a selected test; annotate that exception and why consolidation cannot cover it.
**Principle**: Test = User-observable behavior verifiable in isolated CI environment
ROI is used to **rank candidates within the same test type** (integration candidates against each other, E2E candidates against each other). Cross-type comparison is unnecessary because integration and E2E budgets are selected independently.
For every candidate, record the governing evidence for each ROI input before assigning a value. Use an approved PRD, confirmed requirement context, accepted contract or legal obligation, user-confirmed test value context, Design Doc boundary, and existing-test evidence as applicable. A missing value is `unknown`, not `0`, and an inference is not observed evidence.
When ROI can change candidate ranking, a lane threshold, or budget selection, return the exact missing product input and its decision effect when `test_value_context` has not yet supplied it. After that single input round, apply the supplied facts and retain every remaining value as decision-relevant `unknown` with its numeric score unset. Resolve Defect Detection from repository evidence at the proof boundary and in existing tests. When selection is invariant because the candidate is removed before ROI, is the sole eligible candidate for a reserved journey slot, or all surviving candidates fit an unthresholded budget, record the unknown as `not_decision_relevant` and keep its numeric score unset.
For candidates with a decision-relevant `unknown` after the value-input round, use accepted legal or contractual obligation, explicit connection to the confirmed user or business outcome, distinct Defect Detection evidence, lower lane ownership cost, then source AC order. Select the smallest set that proves the accepted obligations and confirmed outcome boundaries, within the normal lane budgets. Numeric lane thresholds apply to fully scored candidates; this evidence ordering supplies the selection decision for affected candidates. Record the unknown input, evidence checked, and selection effect.
For resolved numeric inputs, use exactly `0`, `5`, or `10`. Legal Requirement remains boolean; a governing-source check that finds no accepted legal, regulatory, contractual, or audit obligation supports `false` and records that checked source.
| Input | Scale | |---|---| | Business Value | 0 = no user/business outcome; 5 = meaningful but non-critical outcome; 10 = core, revenue, safety, or data-integrity outcome | | User Frequency | 0 = unreachable/obsolete; 5 = regular subset of users or runs; 10 = dominant journey or execution path | | Legal Requirement | `true` only when an accepted legal, regulatory, contractual, or audit requirement applies; otherwise `false` | | Defect Detection | 0 = duplicates existing proof; 5 = covers a distinct branch/state; 10 = uniquely detects a critical boundary or cross-service failure
Claude Code can explore a codebase deeply. On non-trivial work, the harder problem is convergence.
Repo: shinpr/claude-code-workflows
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