scan-integration-tests

name	scan-integration-tests
description	[Documentation] Use when scanning integration test base classes, fixtures, helpers, configuration, and service setup.

Codex compatibility note:

• Invoke repository skills with $skill-name in Codex; this mirrored copy rewrites legacy Claude /skill-name references.
• Prefer the plan-hard skill for planning guidance in this Codex mirror.
• Task tracker mandate: BEFORE executing any workflow or skill step, create/update task tracking for all steps and keep it synchronized as progress changes.
• User-question prompts mean to ask the user directly in Codex.
• Ignore Claude-specific mode-switch instructions when they appear.
• Strict execution contract: when a user explicitly invokes a skill, execute that skill protocol as written.
• Subagent authorization: when a skill is user-invoked or AI-detected and its protocol requires subagents, that skill activation authorizes use of the required spawn_agent subagent(s) for that task.
• Do not skip, reorder, or merge protocol steps unless the user explicitly approves the deviation first.
• For workflow skills, execute each listed child-skill step explicitly and report step-by-step evidence.
• If a required step/tool cannot run in this environment, stop and ask the user before adapting.

Codex Project-Reference Loading (No Hooks)

Codex does not receive Claude hook-based doc injection. When coding, planning, debugging, testing, or reviewing, open project docs explicitly using this routing.

Always read:

• docs/project-config.json (project-specific paths, commands, modules, and workflow/test settings)
• docs/project-reference/docs-index-reference.md (routes to the full docs/project-reference/* catalog)
• docs/project-reference/lessons.md (always-on guardrails and anti-patterns)

Situation-based docs:

• Backend/CQRS/API/domain/entity changes: backend-patterns-reference.md, domain-entities-reference.md, project-structure-reference.md
• Frontend/UI/styling/design-system: frontend-patterns-reference.md, scss-styling-guide.md, design-system/README.md
• Spec/test-case planning or TC mapping: feature-docs-reference.md
• Integration test implementation/review: integration-test-reference.md
• E2E test implementation/review: e2e-test-reference.md
• Code review/audit work: code-review-rules.md plus domain docs above based on changed files

Do not read all docs blindly. Start from docs-index-reference.md, then open only relevant files for the task.

Quick Summary

Goal: Scan test codebase → populate docs/project-reference/integration-test-reference.md with test architecture, base classes, fixtures, helpers, configuration patterns, and service-specific setup conventions.

Workflow:

1. Classify — Detect test framework, infrastructure type, and scan mode
2. Scan — Parallel sub-agents discover patterns with file:line evidence
3. Report — Write findings incrementally to report file
4. Generate — Build/update reference doc from report
5. Fresh-Eyes — Round 2 verification validates all examples

Key Rules:

• Generic — works with any test framework (xUnit, NUnit, Jest, Vitest, pytest, JUnit, etc.) MUST ATTENTION detect framework AND infrastructure type FIRST — patterns differ significantly
• Focus on integration/subcutaneous tests (not unit tests) — tests that touch real infrastructure
• Every code example from actual project files with file:line

---

Scan Integration Tests

Phase 0: Detect Framework, Infrastructure & Mode

[BLOCKING] Before any other step, run in parallel:

1. Read docs/project-reference/integration-test-reference.md

   • Detect mode: Init (placeholder) or Sync (populated)
   • In Sync mode: extract section list → skip re-scanning well-documented sections

2. Detect test framework:

Signal	Framework	Key Patterns to Search
*.csproj with xUnit	.NET xUnit	[Fact], [Theory], IAsyncLifetime, IClassFixture
*.csproj with NUnit	.NET NUnit	[Test], [SetUp], [TearDown], [OneTimeSetUp]
package.json with jest	Jest	describe, it, beforeAll, afterAll, jest.mock
package.json with vitest	Vitest	describe, test, vi.mock, beforeEach
package.json with playwright	Playwright	test.describe, page, expect, fixtures
pytest.ini/conftest.py	Python pytest	@pytest.fixture, conftest, @pytest.mark
pom.xml with JUnit	Java JUnit	@Test, @BeforeAll, @SpringBootTest

3. Detect infrastructure approach:

Signal	Approach	Agent Focus
Testcontainers in deps	Docker-based real infra	Container lifecycle, startup time
WebApplicationFactory	In-process server	DI override patterns, test server setup
appsettings.test.json	Config-based test infra	Connection string overrides, env vars
In-memory DB patterns	Fake infra	DB reset strategies, seeding
WaitUntilAsync, polling	Eventual consistency	Async assertion patterns

4. Detect scan mode:

Mode	Condition	Action
Init	Target doc doesn't exist or placeholder	Full scan, create all sections
Sync	Target doc has real content	Diff scan — check for new base classes, helper changes

5. Load test project paths and run prerequisites from docs/project-config.json → integrationTestVerify if available:
   • referenceDocs[] — read these project-specific setup docs before documenting how verification should run
   • runScript / startupScript — inspect to capture Docker/system startup behavior and supported arguments
   • systemCheckCommand — document what readiness check must pass before direct test commands
   • quickRunCommand, testProjectPattern, testProjects[] — use as the source of truth for runner commands and project discovery
   • integrationRules[] — document repeatability/data-integrity gates, including 3 consecutive verification runs without DB reset

Evidence gate: Confidence <60% on framework detection → report uncertainty, ask user before proceeding.

Phase 1: Plan

Create task tracking entries for each sub-agent and each verification step. Do not start Phase 2 without tasks created.

Phase 2: Execute Scan (Parallel Sub-Agents)

Launch 2 general-purpose sub-agents in parallel. Each MUST:

• Write findings incrementally after each service/module — NEVER batch at end
• Cite file:line for every pattern example
• NEVER hardcode test file counts — use grep expressions

All findings → plans/reports/scan-integration-tests-{YYMMDD}-{HHMM}-report.md

Agent 1: Test Infrastructure

Think (Base Class dimension): What does the base class provide — DI container, test server, database connection, fixture lifecycle? Is there a hierarchy (base → service-specific → test)? What must a new test author know to write their first test?

Think (Isolation dimension): How is test isolation achieved — unique IDs per run, database reset, transaction rollback, separate tenant? Can tests run in parallel? What breaks parallelism?

Think (Infrastructure dimension): What must be running for tests to pass? How is the infrastructure provisioned — Docker, in-memory, seeded fixtures? What's the startup cost?

Security flag: If test credentials are found hardcoded in source files (not env vars or secret stores), flag as CRITICAL security issue in report.

• Grep for test base classes (extends.*Test, TestBase, IntegrationTest, IClassFixture, PlatformServiceIntegrationTestWithAssertions)
• Find test fixtures and factories (WebApplicationFactory, TestFixture, conftest, module bootstrappers)
• Discover test configuration (appsettings.test.json, .env.test, test container setup, port bindings)
• Find DI/service registration overrides for testing (mock registrations, test doubles)
• Look for test data builders, seed data patterns, and unique name generators

Agent 2: Test Patterns & Conventions

Think (Assertion dimension): What assertion patterns are used? Is there a waiting/polling mechanism for async operations? Are assertions on specific field values or just "does not throw"?

Think (Data dimension): How is test data created — builders, factories, seed methods? How is uniqueness ensured across runs? Is there a cleanup strategy? Flag direct repository create/update setup as a risk unless it is a valid, idempotent fixture seeder for service-owned reference data. Flag verification guidance as incomplete if it does not require 3 consecutive successful runs without DB reset.

Think (Coverage dimension): Which services have tests? Which are missing? What's the test-to-feature ratio?

• Grep for assertion helpers (WaitUntilAsync, custom assertion extensions, Should* methods)
• Find common test patterns (Arrange-Act-Assert, Given-When-Then, test data flow)
• Discover test categorization (traits, categories, tags — how tests are grouped/filtered)
• Find data uniqueness patterns (Ulid.NewUlid(), Guid.NewGuid(), timestamp suffixes)
• Look for infrastructure interaction patterns (database state verification, queue drain, cache clear)
• Map which services have test projects (coverage distribution) — use grep expressions, not counts

Phase 3: Analyze & Generate

Read full report. Apply fresh-eyes protocol:

Round 1 (main agent): Build section drafts from report findings.

Round 2 (fresh sub-agent, zero memory):

• Does every code example exist at the claimed file:line? (Glob + Grep verify)
• Do base class names in examples match actual class definitions? (Grep verify)
• Are security-sensitive patterns (hardcoded credentials) flagged?
• Are test coverage stats expressed as grep expressions, not hardcoded counts?

Target Sections

Section	Content
Test Architecture	Overall test strategy, framework, infrastructure approach, isolation mechanism
Test Base Classes	Hierarchy with what each base provides; when to use which
Fixtures & Factories	Test fixture setup, DI overrides, module bootstrappers
Test Helpers	Assertion helpers, data builders, wait patterns with examples
Configuration	Test config files, connection strings, environment variables
Service-Specific Setup	Per-service test differences, custom overrides, module registration
Test Data Patterns	How data is created, unique naming, cleanup strategies
New Test Quickstart	Minimal steps to add a new test for a new service
Running Tests	Commands for all, filtered, parallel, CI integration

Phase 4: Write & Verify

1. Write updated doc with <!-- Last scanned: YYYY-MM-DD --> at top
2. Surgical update only — preserve unchanged sections
3. Verify (Glob + Grep): ALL code example file paths exist AND class names match
4. Verify no hardcoded file counts — use grep expressions
5. Verify security flag present if credentials found
6. Report: sections created vs updated, framework detected, coverage gaps

---

[IMPORTANT] Use task tracking to break ALL work into small tasks BEFORE starting — including tasks per file read. Prevents context loss from long files. Simple tasks: ask user whether to skip.

Prerequisites: MUST ATTENTION READ before executing:

Critical Thinking Mindset — Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources, admit uncertainty, self-check output, cross-reference independently. Certainty without evidence = root of all hallucination.

Scan & Update Reference Doc — Surgical updates only, NEVER full rewrite.

1. Read existing doc first — understand structure and manual annotations
2. Detect mode: Placeholder (headings only) → Init. Has content → Sync.
3. Scan codebase (grep/glob) for current patterns
4. Diff findings vs doc — identify stale sections only
5. Update ONLY diverged sections. Preserve manual annotations.
6. Update metadata (date, version) in frontmatter/header
7. NEVER rewrite entire doc. NEVER remove sections without evidence obsolete.

Output Quality — Token efficiency without sacrificing quality.

1. No inventories/counts — stale instantly
2. No directory trees — use 1-line path conventions
3. No TOCs — AI reads linearly
4. One example per pattern — only if non-obvious
5. Lead with answer, not reasoning
6. Sacrifice grammar for concision in reports
7. Unresolved questions at end

AI Mistake Prevention — Failure modes to avoid:

Verify AI-generated content against actual code. AI hallucinates base class names, fixture methods, and assertion helpers. Grep to confirm existence before documenting. Trace full dependency chain after edits. Always trace full chain. Surface ambiguity before coding. NEVER pick silently. NEVER hardcode test file counts. Use grep-expression stats, not hardcoded numbers.

IMPORTANT MUST ATTENTION read existing doc first, scan codebase, diff, surgical update only. Never rewrite entire doc.

IMPORTANT MUST ATTENTION output quality: no counts/trees/TOCs, 1 example per pattern, lead with answer.

MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

Closing Reminders

IMPORTANT MUST ATTENTION break work into small task tracking tasks BEFORE starting IMPORTANT MUST ATTENTION detect framework AND infrastructure type in Phase 0 — patterns depend on both IMPORTANT MUST ATTENTION cite file:line for every code example — NEVER fabricate class or method names IMPORTANT MUST ATTENTION sub-agents write findings incrementally after each service — NEVER batch at end IMPORTANT MUST ATTENTION NEVER hardcode test file counts — use grep expressions IMPORTANT MUST ATTENTION if Round 1 finds issues, Round 2 fresh-eyes is non-negotiable after fixing. Clean Round 1 ENDS the scan.

Anti-Rationalization:

Evasion	Rebuttal
"Framework obvious, skip Phase 0 detection"	Phase 0 is BLOCKING — infrastructure approach determines which patterns to scan
"Smoke-only test assertions are fine"	NEVER document smoke-only as acceptable unless infrastructure is truly unobservable
"Direct repository setup is just test data"	Flag it unless it creates valid owned fixture data; tests should exercise real use cases, not impossible states.
"Base class looks right from memory"	Grep-verify every base class name — AI hallucinates class hierarchies
"Coverage stats obvious from directory scan"	NEVER hardcode counts — use grep expressions that stay accurate as tests are added
"Skip Round 2 even when Round 1 found issues"	Clean Round 1 ends the scan. When issues exist, fresh-eyes mandatory after fixing — main agent rationalizes own fabricated examples.
"Credential security flag not needed"	Hardcoded test creds are a CRITICAL security issue — ALWAYS flag if found

[TASK-PLANNING] Before acting, analyze task scope and break into small todo tasks and sub-tasks using task tracking.

Hookless Prompt Protocol Mirror (Auto-Synced)

Source: .claude/hooks/lib/prompt-injections.cjs + .claude/.ck.json

[WORKFLOW-EXECUTION-PROTOCOL] [BLOCKING] Workflow Execution Protocol — MANDATORY IMPORTANT MUST CRITICAL. Do not skip for any reason.

1. DETECT: Match prompt against workflow catalog
2. ANALYZE: Find best-match workflow AND evaluate if a custom step combination would fit better
3. ASK (REQUIRED FORMAT): Use a direct user question with this structure:
   • Question: "Which workflow do you want to activate?"
   • Option 1: "Activate [BestMatch Workflow] (Recommended)"
   • Option 2: "Activate custom workflow: [step1 → step2 → ...]" (include one-line rationale)
4. ACTIVATE (if confirmed): Call $workflow-start <workflowId> for standard; sequence custom steps manually
5. CREATE TASKS: task tracking for ALL workflow steps
6. EXECUTE: Follow each step in sequence [CRITICAL-THINKING-MINDSET] Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination principle: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination. AI Attention principle (Primacy-Recency): Put the 3 most critical rules at both top and bottom of long prompts/protocols so instruction adherence survives long context windows.

Learned Lessons

Lessons Learned

[CRITICAL] Hard-won project debugging/architecture rules. MUST ATTENTION apply BEFORE forming hypothesis or writing code.

Quick Summary

Goal: Prevent recurrence of known failure patterns — debugging, architecture, naming, AI orchestration, environment.

Top Rules (apply always):

• MUST ATTENTION verify ALL preconditions (config, env, DB names, DI regs) BEFORE code-layer hypothesis
• MUST ATTENTION fix responsible layer — NEVER patch symptom sites with caller-specific defensive code
• MUST ATTENTION use ExecuteInjectScopedAsync for parallel async + repo/UoW — NEVER ExecuteUowTask
• MUST ATTENTION name by PURPOSE not CONTENT — adding member forces rename = abstraction broken
• MUST ATTENTION persist sub-agent findings incrementally after each file — NEVER batch at end
• MUST ATTENTION Windows bash: verify Python alias (where python/where py) — NEVER assume python/python3 resolves

---

Debugging & Root Cause Reasoning

• [2026-04-11] Holistic-first: verify environment before code. Failure → list ALL preconditions (config, env vars, DB names, endpoints, DI regs, credentials, permissions, data prerequisites) → verify each via evidence (grep/cat/query) BEFORE code-layer hypothesis. Worst rabbit holes: diving nearest layer while bug sits elsewhere — e.g., hours debugging "sync timeout", real cause: test appsettings pointing wrong DB. Cheapest check first.
• [2026-04-01] Ask "whose responsibility?" before fixing. Trace: bug in caller (wrong data) or callee (wrong handling)? Fix responsible layer — NEVER patch symptom site masking real issue.
• [2026-04-01] Trace data lifecycle, not error site. Follow data: creation → transformation → consumption. Bug usually where data created wrong, not consumed.
• [2026-04-01] Code is caller-agnostic. Functions/handlers/consumers don't know who invokes them. Comments/guards/messages describe business intent — NEVER reference specific callers (tests, seeders, scripts).

Architecture Invariants

• [2026-03-31] ParallelAsync + repo/UoW MUST use ExecuteInjectScopedAsync, NEVER ExecuteUowTask. ExecuteUowTask creates new UoW but reuses outer DI scope (same DbContext) — parallel iterations sharing non-thread-safe DbContext silently corrupt data. ExecuteInjectScopedAsync creates new UoW + new DI scope (fresh repo per iteration).
• [2026-03-31] Bus message naming MUST include service name prefix — core services NEVER consume feature events. Prefix declares schema ownership (AccountUserEntityEventBusMessage = Accounts owns). Core services (Accounts, Communication) are leaders. Feature services (Growth, Talents) sending to core MUST use {CoreServiceName}...RequestBusMessage — never define own event for core to consume.

Naming & Abstraction

• [2026-04-12] Name PURPOSE not CONTENT — "OrXxx" anti-pattern. HrManagerOrHrOrPayrollHrOperationsPolicy names set members, not what it guards. Add role → rename = broken abstraction. Rule: names express DOES/GUARDS, not CONTAINS. Test: adding/removing member forces rename? YES = content-driven = bad → rename to purpose (e.g., HrOperationsAccessPolicy). Nuance: "Or" fine in behavioral idioms (FirstOrDefault, SuccessOrThrow) — expresses HAPPENS, not membership.

Environment & Tooling

• [2026-04-20] Windows bash: NEVER assume python/python3 resolves — verify alias first. Python may not be in bash PATH under those names. Check: where python / where py. Prefer py (Windows Python Launcher) for one-liners, node if JS alternative exists.

Test-specific lessons → docs/project-reference/integration-test-reference.md Lessons Learned section. Production-code anti-patterns → docs/project-reference/backend-patterns-reference.md Anti-Patterns section. Generic debugging/refactoring reminders → System Lessons in .claude/hooks/lib/prompt-injections.cjs.

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Closing Reminders

• IMPORTANT MUST ATTENTION holistic-first: verify ALL preconditions (config, env, DB names, endpoints, DI regs) BEFORE code-layer hypothesis — cheapest check first
• IMPORTANT MUST ATTENTION fix responsible layer — NEVER patch symptom site; trace caller (wrong data) vs callee (wrong handling), fix root owner
• IMPORTANT MUST ATTENTION parallel async + repo/UoW → ALWAYS ExecuteInjectScopedAsync, NEVER ExecuteUowTask (shared DbContext = silent data corruption)
• IMPORTANT MUST ATTENTION bus message prefix = schema ownership; feature services NEVER define events for core services — use {CoreServiceName}...RequestBusMessage
• IMPORTANT MUST ATTENTION name by PURPOSE — adding/removing member forces rename = broken abstraction
• IMPORTANT MUST ATTENTION sub-agents MUST write findings after each file/section — NEVER batch all findings into one final write
• IMPORTANT MUST ATTENTION Windows bash: NEVER assume python/python3 resolves — run where python/where py first, use py launcher or node

[LESSON-LEARNED-REMINDER] [BLOCKING] Task Planning & Continuous Improvement — MANDATORY. Do not skip.

Break work into small tasks (task tracking) before starting. Add final task: "Analyze AI mistakes & lessons learned".

Extract lessons — ROOT CAUSE ONLY, not symptom fixes:

1. Name the FAILURE MODE (reasoning/assumption failure), not symptom — "assumed API existed without reading source" not "used wrong enum value".
2. Generality test: does this failure mode apply to ≥3 contexts/codebases? If not, abstract one level up.
3. Write as a universal rule — strip project-specific names/paths/classes. Useful on any codebase.
4. Consolidate: multiple mistakes sharing one failure mode → ONE lesson.
5. Recurrence gate: "Would this recur in future session WITHOUT this reminder?" — No → skip $learn.
6. Auto-fix gate: "Could $code-review/$code-simplifier/$security/$lint catch this?" — Yes → improve review skill instead.
7. BOTH gates pass → ask user to run $learn. [TASK-PLANNING] [MANDATORY] BEFORE executing any workflow or skill step, create/update task tracking for all planned steps, then keep it synchronized as each step starts/completes.