seed-test-data

name	seed-test-data
version	2.0.0
description	[Dev Data] Use when you need to implement or enhance test data seeders that simulate QC happy-path scenarios via application-layer commands.
allowed-tools	Read, Write, Edit, Bash, Grep, Glob, TaskCreate, Agent

[BLOCKING] Execute skill steps in declared order. NEVER skip, reorder, or merge steps without explicit user approval. [BLOCKING] Before each step or sub-skill call, update task tracking: set in_progress when step starts, set completed when step ends. [BLOCKING] Every completed/skipped step MUST include brief evidence or explicit skip reason. [BLOCKING] If Task tools are unavailable, create and maintain an equivalent step-by-step plan tracker with the same status transitions.

Quick Summary

Goal: Implement or enhance test data seeders — simulate QC happy-path scenarios via application-layer commands; NEVER direct DB writes.

Workflow:

1. Phase 0 — Detect seeder task type (new / enhance / fix)
2. Step 1 — Discover project seeder patterns, env gate key, count key
3. Step 2 — Analyze feature scope + application commands
4. Step 3 — Find or create seeder file
5. Step 4 — Implement using language-agnostic algorithm
6. Step 5 — Validate against universal rules
7. Review — Fresh sub-agent review round

Key Rules:

• MUST ATTENTION read docs/project-reference/seed-test-data-reference.md and docs/project-config.json (Data Seeders context group) before writing any seeder changes
• NEVER call repository/DB directly for domain data — use application-layer commands
• NEVER duplicate command logic — seeder orchestrates, commands own validation
• ALWAYS gate by environment first; ALWAYS check count before seeding
• ALWAYS read count multiplier from config (NEVER hardcode)
• ALWAYS loop from existing_count to target_count for restart-safety

Phase 0: Detect Seeder Task Type

Before any other step, classify request:

Task Type	Detection	Action
New seeder	No existing seeder for feature area	Create following discovered base class pattern
Enhance existing	Seeder exists, needs new scenarios	Read existing seeder, add without breaking
Fix broken	Seeder fails env gate / idempotency / DI scope	Diagnose via Universal Rules, fix at root
Unknown	Request ambiguous	Ask user — NEVER assume

grep -r "{Feature}Seeder\|{Feature}SeedData\|{Feature}TestData" src/ -l

Universal Seed Data Rules

1. Environment Gate — First check in seeder. Dev/enabled-config only. NEVER production.
2. Command-Based — Calls application commands via full pipeline. Simulates QC manual testing. NEVER direct DB/repo writes for domain entities.
3. No Duplicate Logic — Seeder provides realistic inputs. Commands own validation, domain logic, event side-effects.
4. Idempotency — Check existing count → calculate remaining → seed only difference. Running N times converges to target.
5. Count-Configurable — Reads project config key (discovered Step 1). NEVER hardcode count.
6. Restart-Safe — Idempotency handles restarts: existing count found → seeds only missing remainder.

Protocol

Step 1: Discover Seeder Patterns

Search for project seeder conventions:

# .NET
grep -r "IDataSeeder\|ISeedDataHandler\|ApplicationDataSeeder\|CanSeedTestingData\|SeedingMinimumDummyItemsCount" src/ --include="*.cs" -l

# TypeScript
grep -r "seeder\|SeedData\|DataSeed" src/ --include="*.ts" -l

Record with file:line evidence:

• Seeder base class / interface
• Seeder registration mechanism (DI, module, startup hook)
• Environment gate method/key name
• Count multiplier config key name

Step 1.5: Verify Dev Config Keys

Confirm dev config has both env gate key and count key. If absent, add following project's dev config convention.

Step 2: Feature Scope Analysis

Identify before writing any code:

1. Feature area — domain entity/aggregate being seeded
2. Application commands — grep -r "{Feature}*Command" src/ --include="*.cs" -l
3. Dependencies — data must exist (users, orgs, prerequisite records)
4. Scenarios — 3–5 realistic variations (standard, boundary, multi-actor)
5. Target count — clarify: 1 scenario or N repetitions per scenario

Step 3: Find or Create Seeder

grep -r "{Feature}TestSeeder\|{Feature}SeedingHelper\|{Feature}TestDataSeeder" src/ -l

• Exists → enhance with new scenarios, do NOT break existing ones
• Absent → create following discovered base class pattern

Step 4: Implement

Algorithm (language-agnostic):

seeder():
  if not is_development_environment(): return
  if not seed_enabled_in_config(): return
  target = config.get("SeedCount")
  if target <= 0: return
  existing = count_by_seeder_marker()
  if existing >= target: return
  for i from existing to target:
    call_application_command(build_scenario_input(i))

Seeder marker — stable predicate identifying seeded vs user data:

• Email prefix, created-by field, name prefix, or dedicated boolean flag
• MUST be deterministic across restarts

Step 5: Validate

MUST ATTENTION verify all before complete:

• MUST ATTENTION environment gate is FIRST check — file:line evidence required
• MUST ATTENTION count-before-seed idempotency gate present — file:line evidence
• MUST ATTENTION loop starts at existing_count, not 0 — file:line evidence
• MUST ATTENTION only application-layer commands used for domain entities — NEVER repo/DB
• MUST ATTENTION no business logic or validation duplicated in seeder
• MUST ATTENTION seeder registered via project DI mechanism — file:line evidence
• MUST ATTENTION count config key read correctly (zero → no-op, NEVER hardcoded)
• MUST ATTENTION scoped DI per iteration — shared scope = DbContext/session corruption

Sub-Agent Routing

Task	Sub-Agent	When
Discover seeders + commands across large codebase	general-purpose	Steps 1-2
Review seeder compliance	code-reviewer	Round 1 post-implementation
Seeder handles credentials/PII	security-auditor	Security-sensitive patterns
Seeder runs 1000+ records	performance-optimizer	Performance-intensive

All sub-agent prompts MUST include:

Graph DB active. After grep finds key files, run:
python .claude/scripts/code_graph trace <file> --direction both --json
Pattern: grep → trace → grep verify.

Anti-Patterns

Anti-Pattern	Correct
Direct repo insert for domain entities	Call application command
Seeder validates business rules	Command owns validation; seeder provides valid inputs
No idempotency check	Check count first; seed only remaining
Hardcoded count (for i in 0..10)	Read count from config key (discovered Step 1)
No environment gate	Check project env gate key first
Shared DI scope across loop iterations	Use project's scoped DI per iteration (prevents DbContext corruption)
Batch-all-then-write sub-agent findings	Persist findings per file; NEVER batch at end

Review Loop

Round 1: After implementation, spawn fresh code-reviewer sub-agent with zero memory of implementation:

Review seeder at [file:path]. Verify with file:line evidence for each:
1. Environment gate is FIRST check
2. Idempotency: count-before-seed pattern present
3. Loop starts at existing_count not 0
4. Zero application-layer command bypasses (direct repo/DB = FAIL)
5. No hardcoded count — config key read
6. Scoped DI per iteration
Report: PASS or FAIL with file:line for each finding.

Round 2: If FAIL → fix → new fresh sub-agent. Max 3 rounds → escalate to user. NEVER reuse sub-agent across rounds. A clean round ENDS the review; a round with issues triggers fix → fresh sub-agent re-review.

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Workflow Recommendation

MUST ATTENTION — NOT IN WORKFLOW YET: Use AskUserQuestion:

1. Activate workflow-seed-test-data (Recommended) — scout → investigate → seed-test-data → review-changes → code-simplifier → docs-update
2. Execute /seed-test-data directly — run this skill standalone

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Next Steps

MUST ATTENTION after completing: use AskUserQuestion — do NOT skip:

• "/workflow-review-changes (Recommended)" — review all changes before commit
• "/integration-test" — write tests verifying idempotency and count compliance
• "Skip, continue manually" — user decides

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[IMPORTANT] TaskCreate for ALL tasks BEFORE starting. For simple tasks, ask user whether to skip.

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: 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.

Understand Code First — HARD-GATE: Do NOT write, plan, or fix until you READ existing code.

1. Search 3+ similar patterns (grep/glob) — cite file:line evidence
2. Read existing files in target area — understand structure, base classes, conventions
3. Run python .claude/scripts/code_graph trace <file> --direction both --json when .code-graph/graph.db exists
4. Map dependencies via connections or callers_of — know what depends on your target
5. Write investigation to .ai/workspace/analysis/ for non-trivial tasks (3+ files)
6. Re-read analysis file before implementing — never work from memory alone
7. NEVER invent new patterns when existing ones work — match exactly or document deviation

BLOCKED until: - [ ] Read target files - [ ] Grep 3+ patterns - [ ] Graph trace (if graph.db exists) - [ ] Assumptions verified with evidence

Evidence-Based Reasoning — Speculation is FORBIDDEN. Every claim needs proof.

1. Cite file:line, grep results, or framework docs for EVERY claim
2. Declare confidence: >80% act freely, 60-80% verify first, <60% DO NOT recommend
3. Cross-service validation required for architectural changes
4. "I don't have enough evidence" is valid and expected output

BLOCKED until: - [ ] Evidence file path (file:line) - [ ] Grep search performed - [ ] 3+ similar patterns found - [ ] Confidence level stated

Forbidden without proof: "obviously", "I think", "should be", "probably", "this is because" If incomplete → output: "Insufficient evidence. Verified: [...]. Not verified: [...]."

AI Mistake Prevention — Failure modes to avoid on every task:

Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

IMPORTANT MUST ATTENTION search 3+ existing patterns and read code BEFORE writing any seeder.

MUST ATTENTION cite file:line for every claim; declare confidence; "I don't have enough evidence" is valid output.

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.

Prompt-Enhance Closing Anchors

IMPORTANT MUST ATTENTION follow declared step order for this skill; NEVER skip, reorder, or merge steps without explicit user approval IMPORTANT MUST ATTENTION for every step/sub-skill call: set in_progress before execution, set completed after execution IMPORTANT MUST ATTENTION every skipped step MUST include explicit reason; every completed step MUST include concise evidence IMPORTANT MUST ATTENTION if Task tools unavailable, maintain an equivalent step-by-step plan tracker with synchronized statuses

Closing Reminders

IMPORTANT MUST ATTENTION TaskCreate — break all work into tasks BEFORE starting IMPORTANT MUST ATTENTION NEVER call repo/DB directly — use application-layer commands IMPORTANT MUST ATTENTION ALWAYS gate by environment FIRST; ALWAYS check count before seeding IMPORTANT MUST ATTENTION loop from existing_count to target_count — NEVER from 0 IMPORTANT MUST ATTENTION scoped DI per iteration — shared DI scope = silent DbContext corruption IMPORTANT MUST ATTENTION fresh sub-agent re-review required ONLY after a fix cycle. Clean Round 1 ENDS the review.

Anti-Rationalization:

Evasion	Rebuttal
"Simple seeder, skip review loop"	Idempotency bugs are silent. Run Round 1 always.
"Already know the base class"	Show file:line. No proof = no knowledge.
"Environment gate is obvious"	Verify it's FIRST check with file:line evidence.
"Just hardcode count for now"	NEVER — config key required. Find it in Step 1.
"No graph.db, skip trace"	Use grep-only trace. Still run 3+ pattern search.
"Existing scenarios look fine, skip enhance"	Read all scenarios; enhancement may conflict — verify first.

[TASK-PLANNING] Before acting, break task into small todo tasks using TaskCreate.