[IMPORTANT] Use

TaskCreate

to break ALL work into small tasks BEFORE starting.

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.

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.

Prerequisites: MUST ATTENTION READ before executing:

Web Research — Structured web search for evidence gathering.

1. Form 3-5 specific search queries (not generic questions)
2. Use WebSearch for each query, collect top 3-5 sources
3. Validate source credibility (official docs > blogs > forums)
4. Cross-validate claims across 2+ sources before citing
5. Write findings to research report with source URLs

NEVER cite a single source as authoritative. Always cross-validate.

OOP & DRY Enforcement: MANDATORY IMPORTANT MUST ATTENTION — flag duplicated patterns that should be extracted to a base class, generic, or helper. Classes in the same group or suffix (ex *Entity, *Dto, *Service, etc...) MUST ATTENTION inherit a common base (even if empty now — enables future shared logic and child overrides). Verify project has code linting/analyzer configured for the stack.

Quick Summary

Goal: Review knowledge artifacts for quality, completeness, and protocol compliance.

Workflow:

1. Read artifact — Load the knowledge report/course/strategy
2. Template compliance — Verify all enforced sections present
3. Citation audit — Check inline citations and source table
4. Confidence check — Verify scores match evidence
5. Output review — Summary with pass/warn/fail per check

Key Rules:

• Every section from template must be present and non-empty
• Every factual claim must have inline citation
• Confidence scores must match evidence basis
• READ-ONLY — do not modify the artifact

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Adversarial Review Mindset (NON-NEGOTIABLE)

Default stance: SKEPTIC challenging research quality, not confirming research completeness.

Source confirmation bias trap: AI naturally gravitates toward sources that confirm its working hypothesis. The knowledge artifact was built iteratively — by the time it's complete, the framing is locked in. This section forces challenge of both the sources AND the framing.

Adversarial Techniques (apply ALL before concluding)

1. Source Bias Detection For the top 3 claims in the artifact: "What sources CONTRADICT this claim?" If no contradicting source is cited — either the reviewer didn't look, or the evidence is truly one-sided. Ask: "What would a skeptic of this conclusion cite?" If no counterevidence is addressed, the confidence score is inflated.

2. Confidence Calibration Challenge For each confidence score ≥ 80%: "What would need to be true for this confidence to be wrong?" High confidence is only warranted when: (a) multiple independent sources agree, (b) contradicting evidence is addressed, (c) the methodology is sound. Challenge any score that rests on a single source or on undisclosed assumptions.

3. Alternative Conclusion Check Given the same evidence, what DIFFERENT conclusion could a reasonable expert reach? If the artifact does not address at least one credible alternative interpretation, the analysis is incomplete. State the strongest alternative conclusion.

4. Cherry-Picking Detection Count the sources that support the main conclusion vs. sources that challenge it. If the ratio is > 3:1 in favor of supporting sources without explicit explanation of why contradicting sources were discounted — flag cherry-picking.

5. Pre-Mortem Assume the recommendation in this artifact is implemented and fails. Write the most plausible failure scenario given the research limitations. If the artifact doesn't acknowledge this failure mode — it's missing a risk section.

6. Contrarian Pass Before writing any verdict, generate at least 2 sentences arguing the OPPOSITE conclusion about the artifact's quality. Then decide which argument is stronger.

Forbidden Patterns

• "Sources are cited" → Presence of citations ≠ quality. Do they actually support the claim?
• "Confidence scores look reasonable" → What would LOWER the confidence score? Name it.
• "Comprehensive coverage" → What perspective is MISSING from this research?
• "Recommendations are actionable" → On what evidence? What's the confidence of the evidence chain?
• Approving a knowledge artifact without challenging the evidence quality → Forbidden.

Anti-Bias Gate (MANDATORY before finalizing verdict)

• Found at least 1 contradicting source per major claim (or flagged its absence)
• Challenged at least 1 confidence score ≥ 80% with a stress test
• Stated the strongest alternative conclusion from the same evidence
• Checked source balance (supporting vs. contradicting ratio)
• Ran pre-mortem on the main recommendation
• Generated at least 2 sentences arguing the opposite verdict

If any box is unchecked → adversarial review incomplete. Go back.

Knowledge Review

Review Checklist

1. Template Compliance

2. Citation Audit

[N]

[N]

[N]

[N]

3. Confidence Accuracy

4. Source Quality

5. Knowledge Gaps

6. Cross-Validation

7. Actionability

Output Format

## Knowledge Review Result

**Status:** PASS | WARN | FAIL
**Artifact:** {path}

### Checks (N/7 passed)

- [x] Template compliance
- [x] Citation audit
- [ ] Confidence accuracy — {issue}
- [ ] Source quality — {issue}
      ...

### Issues

- {specific issues found}

### Verdict

{APPROVED | REVISE | BLOCKED}

Round 2: Focused Re-Review (MANDATORY)

Deep Multi-Round Review — Escalating rounds. Round 1 in main session. Round 2+ and EVERY recursive re-review iteration MUST use a fresh sub-agent.

Round 1: Main-session review. Read target files, build understanding, note issues. Output baseline findings.

Round 2: MANDATORY fresh sub-agent review — see

SYNC:fresh-context-review

for the spawn mechanism and

SYNC:review-protocol-injection

for the canonical Agent prompt template. The sub-agent re-reads ALL files from scratch with ZERO Round 1 memory. It must catch:

• Cross-cutting concerns missed in Round 1
• Interaction bugs between changed files
• Convention drift (new code vs existing patterns)
• Missing pieces that should exist but don't
• Subtle edge cases the main session rationalized away

Round 3+ (recursive after fixes): After ANY fix cycle, MANDATORY fresh sub-agent re-review. Spawn a NEW Agent tool call each iteration — never reuse Round 2's agent. Each new agent re-reads ALL files from scratch with full protocol injection. Continue until PASS or 3 fresh-subagent rounds max, then escalate to user via

AskUserQuestion

.

Rules:

• NEVER declare PASS after Round 1 alone
• NEVER reuse a sub-agent across rounds — every iteration spawns a NEW Agent call
• Main agent READS sub-agent reports but MUST NOT filter, reinterpret, or override findings
• Max 3 fresh-subagent rounds per review — if still FAIL, escalate via

  AskUserQuestion

  (do NOT silently loop)
• Track round count in conversation context (session-scoped)
• Final verdict must incorporate ALL rounds

Report must include

## Round N Findings (Fresh Sub-Agent)

for every round N≥2.

Fresh Sub-Agent Review — Eliminate orchestrator confirmation bias via isolated sub-agents.

Why: The main agent knows what it (or

/cook

) just fixed and rationalizes findings accordingly. A fresh sub-agent has ZERO memory, re-reads from scratch, and catches what the main agent dismissed. Sub-agent bias is mitigated by (1) fresh context, (2) verbatim protocol injection, (3) main agent not filtering the report.

When: Round 2 of ANY review AND every recursive re-review iteration after fixes. NOT needed when Round 1 already PASSes with zero issues.

How:

1. Spawn a NEW

   Agent

   tool call — use

   code-reviewer

   subagent_type for code reviews,

   general-purpose

   for plan/doc/artifact reviews
2. Inject ALL required review protocols VERBATIM into the prompt — see

   SYNC:review-protocol-injection

   for the full list and template. Never reference protocols by file path; AI compliance drops behind file-read indirection (see

   SYNC:shared-protocol-duplication-policy

   )
3. Sub-agent re-reads ALL target files from scratch via its own tool calls — never pass file contents inline in the prompt
4. Sub-agent writes structured report to

   plans/reports/{review-type}-round{N}-{date}.md

5. Main agent reads the report, integrates findings into its own report, DOES NOT override or filter

Rules:

• NEVER reuse a sub-agent across rounds — every iteration spawns a NEW

  Agent

  call
• NEVER skip fresh-subagent review because "last round was clean" — every fix triggers a fresh round
• Max 3 fresh-subagent rounds per review — escalate via

  AskUserQuestion

  if still failing; do NOT silently loop or fall back to any prior protocol
• Track iteration count in conversation context (session-scoped, no persistent files)

Review Protocol Injection — Every fresh sub-agent review prompt MUST embed 10 protocol blocks VERBATIM. The template below has ALL 10 bodies already expanded inline. Copy the template wholesale into the Agent call's

prompt

field at runtime, replacing only the

{placeholders}

in Task / Round / Reference Docs / Target Files / Output sections with context-specific values. Do NOT touch the embedded protocol sections.

Why inline expansion: Placeholder markers would force file-read indirection at runtime. AI compliance drops significantly behind indirection (see

SYNC:shared-protocol-duplication-policy

). Therefore the template carries all 10 protocol bodies pre-embedded.

Subagent Type Selection

• code-reviewer

  — for code reviews (reviewing source files, git diffs, implementation)

• general-purpose

  — for plan / doc / artifact reviews (reviewing markdown plans, docs, specs)

Canonical Agent Call Template (Copy Verbatim)

Agent({
  description: "Fresh Round {N} review",
  subagent_type: "code-reviewer",
  prompt: `
## Task
{review-specific task — e.g., "Review all uncommitted changes for code quality" | "Review plan files under {plan-dir}" | "Review integration tests in {path}"}

## Round
Round {N}. You have ZERO memory of prior rounds. Re-read all target files from scratch via your own tool calls. Do NOT trust anything from the main agent beyond this prompt.

## Protocols (follow VERBATIM — these are non-negotiable)

### 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) provided; 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: [...]."

### Bug Detection
MUST check categories 1-4 for EVERY review. Never skip.
1. Null Safety: Can params/returns be null? Are they guarded? Optional chaining gaps? .find() returns checked?
2. Boundary Conditions: Off-by-one (< vs <=)? Empty collections handled? Zero/negative values? Max limits?
3. Error Handling: Try-catch scope correct? Silent swallowed exceptions? Error types specific? Cleanup in finally?
4. Resource Management: Connections/streams closed? Subscriptions unsubscribed on destroy? Timers cleared? Memory bounded?
5. Concurrency (if async): Missing await? Race conditions on shared state? Stale closures? Retry storms?
6. Stack-Specific: JS: === vs ==, typeof null. C#: async void, missing using, LINQ deferred execution.
Classify: CRITICAL (crash/corrupt) → FAIL | HIGH (incorrect behavior) → FAIL | MEDIUM (edge case) → WARN | LOW (defensive) → INFO.

### Design Patterns Quality
Priority checks for every code change:
1. DRY via OOP: Same-suffix classes (*Entity, *Dto, *Service) MUST share base class. 3+ similar patterns → extract to shared abstraction.
2. Right Responsibility: Logic in LOWEST layer (Entity > Domain Service > Application Service > Controller). Never business logic in controllers.
3. SOLID: Single responsibility (one reason to change). Open-closed (extend, don't modify). Liskov (subtypes substitutable). Interface segregation (small interfaces). Dependency inversion (depend on abstractions).
4. After extraction/move/rename: Grep ENTIRE scope for dangling references. Zero tolerance.
5. YAGNI gate: NEVER recommend patterns unless 3+ occurrences exist. Don't extract for hypothetical future use.
Anti-patterns to flag: God Object, Copy-Paste inheritance, Circular Dependency, Leaky Abstraction.

### Logic & Intention Review
Verify WHAT code does matches WHY it was changed.
1. Change Intention Check: Every changed file MUST serve the stated purpose. Flag unrelated changes as scope creep.
2. Happy Path Trace: Walk through one complete success scenario through changed code.
3. Error Path Trace: Walk through one failure/edge case scenario through changed code.
4. Acceptance Mapping: If plan context available, map every acceptance criterion to a code change.
NEVER mark review PASS without completing both traces (happy + error path).

### Test Spec Verification
Map changed code to test specifications.
1. From changed files → find TC-{FEAT}-{NNN} in docs/business-features/{Service}/detailed-features/{Feature}.md Section 15.
2. Every changed code path MUST map to a corresponding TC (or flag as "needs TC").
3. New functions/endpoints/handlers → flag for test spec creation.
4. Verify TC evidence fields point to actual code (file:line, not stale references).
5. Auth changes → TC-{FEAT}-02x exist? Data changes → TC-{FEAT}-01x exist?
6. If no specs exist → log gap and recommend /tdd-spec.
NEVER skip test mapping. Untested code paths are the #1 source of production bugs.

### Fix-Layer Accountability
NEVER fix at the crash site. Trace the full flow, fix at the owning layer. The crash site is a SYMPTOM, not the cause.
MANDATORY before ANY fix:
1. Trace full data flow — Map the complete path from data origin to crash site across ALL layers (storage → backend → API → frontend → UI). Identify where bad state ENTERS, not where it CRASHES.
2. Identify the invariant owner — Which layer's contract guarantees this value is valid? Fix at the LOWEST layer that owns the invariant, not the highest layer that consumes it.
3. One fix, maximum protection — If fix requires touching 3+ files with defensive checks, you are at the wrong layer — go lower.
4. Verify no bypass paths — Confirm all data flows through the fix point. Check for direct construction skipping factories, clone/spread without re-validation, raw data not wrapped in domain models, mutations outside the model layer.
BLOCKED until: Full data flow traced (origin → crash); Invariant owner identified with file:line evidence; All access sites audited (grep count); Fix layer justified (lowest layer that protects most consumers).
Anti-patterns (REJECT): "Fix it where it crashes" (crash site ≠ cause site, trace upstream); "Add defensive checks at every consumer" (scattered defense = wrong layer); "Both fix is safer" (pick ONE authoritative layer).

### Rationalization Prevention
AI skips steps via these evasions. Recognize and reject:
- "Too simple for a plan" → Simple + wrong assumptions = wasted time. Plan anyway.
- "I'll test after" → RED before GREEN. Write/verify test first.
- "Already searched" → Show grep evidence with file:line. No proof = no search.
- "Just do it" → Still need TaskCreate. Skip depth, never skip tracking.
- "Just a small fix" → Small fix in wrong location cascades. Verify file:line first.
- "Code is self-explanatory" → Future readers need evidence trail. Document anyway.
- "Combine steps to save time" → Combined steps dilute focus. Each step has distinct purpose.

### Graph-Assisted Investigation
MANDATORY when .code-graph/graph.db exists.
HARD-GATE: MUST run at least ONE graph command on key files before concluding any investigation.
Pattern: Grep finds files → trace --direction both reveals full system flow → Grep verifies details.
- Investigation/Scout: trace --direction both on 2-3 entry files
- Fix/Debug: callers_of on buggy function + tests_for
- Feature/Enhancement: connections on files to be modified
- Code Review: tests_for on changed functions
- Blast Radius: trace --direction downstream
CLI: python .claude/scripts/code_graph {command} --json. Use --node-mode file first (10-30x less noise), then --node-mode function for detail.

### 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.

## Reference Docs (READ before reviewing)
- docs/project-reference/code-review-rules.md
- {skill-specific reference docs — e.g., integration-test-reference.md for integration-test-review; backend-patterns-reference.md for backend reviews; frontend-patterns-reference.md for frontend reviews}

## Target Files
{explicit file list OR "run git diff to see uncommitted changes" OR "read all files under {plan-dir}"}

## Output
Write a structured report to plans/reports/{review-type}-round{N}-{date}.md with sections:
- Status: PASS | FAIL
- Issue Count: {number}
- Critical Issues (with file:line evidence)
- High Priority Issues (with file:line evidence)
- Medium / Low Issues
- Cross-cutting findings

Return the report path and status to the main agent.
Every finding MUST have file:line evidence. Speculation is forbidden.
`
})

Rules

• DO copy the template wholesale — including all 10 embedded protocol sections
• DO replace only the

  {placeholders}

  in Task / Round / Reference Docs / Target Files / Output sections with context-specific content
• DO choose

  code-reviewer

  subagent_type for code reviews and

  general-purpose

  for plan / doc / artifact reviews
• DO NOT paraphrase, summarize, or skip any protocol section
• DO NOT pass file contents inline — the sub-agent reads via its own tool calls so it has a fresh context
• DO NOT reference protocols by file path or tag name — the bodies are already embedded above
• DO NOT introduce placeholder markers for the protocols — they must stay literally expanded

After completing Round 1 evaluation, execute a second full review round:

1. Re-read the Round 1 verdict and checklist results
2. Re-evaluate ALL checklist items — do NOT rely on Round 1 memory
3. Challenge Round 1 PASS items: "Is this really PASS? Did I verify citations and confidence?"
4. Focus on what Round 1 typically misses:
   • Citation accuracy (do sources actually say what's claimed?)
   • Confidence calibration (are percentages realistic?)
   • Knowledge gaps that weren't flagged
   • Template compliance shortcuts
5. Update verdict if Round 2 found new issues
6. Final verdict must incorporate findings from BOTH rounds

Closing Reminders

• IMPORTANT MUST ATTENTION break work into small todo tasks using

  TaskCreate

  BEFORE starting
• IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
• IMPORTANT MUST ATTENTION cite

  file:line

  evidence for every claim (confidence >80% to act)
• IMPORTANT MUST ATTENTION add a final review todo task to verify work quality
• IMPORTANT MUST ATTENTION execute two review rounds (Round 1: understand, Round 2: catch missed issues) MANDATORY IMPORTANT MUST ATTENTION READ the following files before starting: <!-- SYNC:web-research:reminder -->
• IMPORTANT MUST ATTENTION cite 2+ independent sources per claim. NEVER fabricate — "No evidence found" is valid output. <!-- /SYNC:web-research:reminder --> <!-- SYNC:double-round-trip-review:reminder -->
• MANDATORY IMPORTANT MUST ATTENTION execute TWO review rounds. Round 2 delegates to fresh code-reviewer sub-agent (zero prior context) — never skip or combine with Round 1. <!-- /SYNC:double-round-trip-review:reminder --> <!-- SYNC:critical-thinking-mindset:reminder -->
• MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact. <!-- /SYNC:critical-thinking-mindset:reminder --> <!-- SYNC:ai-mistake-prevention:reminder -->
• MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction. <!-- /SYNC:ai-mistake-prevention:reminder -->