code-simplifier（代码简化）

[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.

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. For simple tasks, MUST ATTENTION 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.

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:

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

Design Patterns Quality — Priority checks for every code change: 1. DRY via OOP: Identify classes/modules with the same purpose, naming pattern, or lifecycle. Apply your knowledge of the project's language/framework to determine the idiomatic abstraction (base class, mixin, trait, protocol, decorator). 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. Serial Attention for Design Quality — DO NOT scan all quality concerns simultaneously. Split attention misses violations that focused passes catch. 1. Identify applicable dimensions — Based on the code's language, domain, and patterns, determine which quality dimensions apply: DRY, SOLID principles (SRP/OCP/LSP/ISP/DIP), OOP idioms, cohesion/coupling, GRASP, Law of Demeter, CQRS invariants, etc. Your list is NOT fixed — derive from what the code actually does. 2. One focused pass per dimension — Dedicate single-focus attention to EACH dimension in sequence. Do NOT mix concerns across passes. 3. Threshold: 3+ similar patterns = MANDATORY extraction — Not optional suggestion. Flag as mandatory structural fix requiring action. 4. 2+ violations of same kind = structural finding — Report as "pattern problem" needing architectural resolution, not a list of individual instances.

• docs/project-reference/domain-entities-reference.md — domain entity catalog, relationships, cross-service sync (read when task involves business entities/models) (content auto-injected by hook — check for [Injected:...] header before reading)

External Memory: Complex/lengthy work → write findings to plans/reports/. Prevents context loss, serves as deliverable.

Evidence Gate: MANDATORY IMPORTANT MUST ATTENTION — every claim, finding, recommendation requires file:line proof or traced evidence (confidence >80% to act, <80% verify first).

OOP & DRY Enforcement: MANDATORY IMPORTANT MUST ATTENTION — flag duplicated patterns for base class extraction. Same-suffix classes (*Entity, *Dto, *Service) MUST ATTENTION inherit common base. Verify stack has linting/analyzer configured.

Quick Summary

Goal: Simplify and refine code for clarity, consistency, maintainability — preserving all functionality.

MANDATORY IMPORTANT MUST ATTENTION Plan task to READ: - docs/project-reference/code-review-rules.md — anti-patterns, review checklists (READ FIRST) - project-structure-reference.md — project patterns/structure If not found, search for: project documentation, coding standards, architecture docs.

Workflow:

1. Phase 0: Detect — Classify artifact type (backend/frontend/test/config) and scope
2. Identify Targets — Recent git changes or specified files (skip generated/vendor)
3. Analyze — Apply simplification dimensions (see below)
4. Apply — One refactoring type at a time following KISS/DRY/YAGNI
5. Verify — Run related tests, confirm no behavior changes
6. Fresh-Context Review — Spawn code-reviewer sub-agent (MANDATORY)

Key Rules:

• Preserve all existing functionality — no behavior changes
• Follow platform patterns (entity expressions, fluent helpers, store base, BEM)
• Tests pass after every change
• NEVER apply simplification when unsure it preserves behavior

Frontend/UI Context (if applicable)

When task involves frontend/UI changes:

UI System Context — For ANY task touching .ts, .html, .scss, or .css files: MUST ATTENTION READ before implementing: 1. docs/project-reference/frontend-patterns-reference.md — component base classes, stores, forms 2. docs/project-reference/scss-styling-guide.md — BEM methodology, SCSS variables, mixins, responsive 3. docs/project-reference/design-system/README.md — design tokens, component inventory, icons Reference docs/project-config.json for project-specific paths.

Phase 0: Artifact Detection

MUST ATTENTION classify before simplifying — detection drives focus and sub-agent routing:

Sub-agent routing by artifact:

Simplification Mindset

Skeptical-first: Verify before simplifying. Every change needs proof it preserves behavior.

• NEVER assume code redundant — trace call paths and read implementations first
• Before removing/replacing: grep all usages confirming nothing depends on current form
• Before flagging convention violation: grep 3+ existing examples — codebase convention wins
• Every simplification requires file:line evidence of what was verified
• If unsure whether simplification preserves behavior → DO NOT apply

Simplification Dimensions

Dimension-based reasoning replaces fixed checklists. Each dimension has a Think: prompt forcing first-principles reasoning.

Dimension 1: Readability

Think: Would a new engineer understand this in 30 seconds? What forces multiple file traces?

• Schema visibility: functions computing data structures need output-shape comment
• Non-obvious pipelines: A→B→C transformations need brief pipeline explanation
• Self-documenting signatures: params explain role; remove unused params
• Magic values: replace unexplained numbers/strings with named constants
• Naming clarity: names reveal intent without reading implementation

Dimension 2: DRY & Abstraction

Think: Pattern appearing ≥3 places? What base class/generic eliminates duplication?

• Same-suffix classes (*Entity, *Dto, *Service) → shared base
• Repeated logic blocks → extract to helper/extension method
• YAGNI gate: NEVER extract for hypothetical future use — 3+ occurrences required

Dimension 3: Right Responsibility

Think: Logic in lowest layer that can own it? Could moving it down enable reuse?

• Entity/Model → Domain Service → Application Service → Controller (logic belongs lowest)
• Business logic in controllers → move down
• Mapping in handlers → move to DTO methods

Dimension 4: Complexity Reduction

Think: What is cognitive load? Can nesting/conditionals flatten?

• Nesting >3 → refactor (early returns, extract methods)
• Methods >20 lines → extract
• Complex conditionals → flatten or Strategy pattern (3+ branching occurrences only)

Dimension 5: Database Performance

MANDATORY IMPORTANT MUST ATTENTION 1. Paging: ALL list queries MUST use pagination. NEVER unbounded GetAll(), ToList(), Find() without Skip/Take or cursor-based paging. 2. Indexes: ALL filter fields, foreign keys, sort columns MUST have database indexes. Entity expressions must match index field order. Collections need index management methods.

Project Patterns

Backend

• Extract entity static expressions (search: entity expression pattern)
• Use fluent helpers (search: fluent helper pattern in docs/project-reference/backend-patterns-reference.md)
• Move mapping to DTO mapping methods (search: DTO mapping pattern)
• Use project validation fluent API (see docs/project-reference/backend-patterns-reference.md)
• Verify entity expressions have database indexes
• Verify document DB collections have index management methods

Frontend

• Use project store base (search: store base class) for state management
• Apply subscription cleanup (search: subscription cleanup pattern) to all subscriptions
• BEM class naming on ALL template elements
• Use platform base classes (search: base component class, store component base class)

Graph Intelligence (MANDATORY if graph.db exists)

Before simplifying, trace what depends on target:

python .claude/scripts/code_graph trace <file> --direction downstream --json

Verify simplified code preserves same interface for all traced consumers. Cross-service MESSAGE_BUS consumers are especially fragile — may depend on exact message shape.

Additional queries:

• Verify no callers break: python.claude/scripts/code_graph query callers_of <function> --json
• Check dependents: python.claude/scripts/code_graph query importers_of <module> --json
• Batch analysis: python.claude/scripts/code_graph batch-query file1 file2 --json

Execution

Agent(subagent_type="code-simplifier", prompt="Review and simplify [target files]")

Example:

// Before
function getData() {
    const result = fetchData();
    if (result !== null && result !== undefined) {
        return result;
    } else {
        return null;
    }
}

// After
function getData() {
    return fetchData() ?? null;
}

Constraints

• Preserve functionality — no behavior changes
• Tests passing — verify after every change
• Follow patterns — use platform conventions, never invent
• Doc staleness — cross-ref changed files against feature docs, test specs, READMEs; flag updates needed

Shared Protocol Duplication Policy — Inline protocol content in skills (wrapped in <!-- SYNC:tag -->) is INTENTIONAL duplication. Do NOT extract, deduplicate, or replace with file references. AI compliance drops significantly when protocols are behind file-read indirection. To update: edit .claude/skills/shared/sync-inline-versions.md first, then grep SYNC:protocol-name and update all occurrences.

Fresh Sub-Agent Verification (MANDATORY after simplifications in a review workflow)

After simplifications applied, verification requires fresh sub-agent review to eliminate confirmation bias. See SYNC blocks below.

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

When used standalone (outside a review workflow), run /workflow-review-changes to trigger the full review cycle with fresh sub-agent re-review.

Workflow Recommendation

MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS: If NOT already in workflow, use AskUserQuestion to ask user. Do NOT decide this is "simple enough to skip" — the user decides: 1. Activate quality-audit workflow (Recommended) — code-simplifier → review-changes → code-review 2. Execute /code-simplifier directly — run standalone

Next Steps

MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS after completing, use AskUserQuestion:

• "/workflow-review-changes (Recommended)" — Review all changes before commit
• "/code-review" — Full code review
• "Skip, continue manually" — user decides

AI Agent Integrity Gate (NON-NEGOTIABLE)

Completion ≠ Correctness. Before reporting work done, prove it: 1. Grep every removed name. Extraction/rename/delete → grep confirms 0 dangling refs across ALL file types. 2. Ask WHY before changing. Existing values intentional until proven otherwise. No "fix" without traced rationale. 3. Verify ALL outputs. One build passing ≠ all builds passing. Check every affected stack. 4. Evaluate pattern fit. Copying nearby code? Verify preconditions match — same scope, lifetime, base class, constraints. 5. New artifact = wired artifact. Created? Prove registered, imported, reachable by all consumers.

Closing Reminders

• MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks via TaskCreate BEFORE starting
• MANDATORY IMPORTANT MUST ATTENTION validate decisions with user via AskUserQuestion — never auto-decide
• MANDATORY IMPORTANT MUST ATTENTION add final review task to verify work quality
• MANDATORY IMPORTANT MUST ATTENTION READ docs/project-reference/code-review-rules.md FIRST
• MANDATORY IMPORTANT MUST ATTENTION search 3+ existing patterns and read code BEFORE modification. Run graph trace when graph.db exists.
• MANDATORY IMPORTANT MUST ATTENTION check DRY via OOP (same-suffix → base class), right responsibility (lowest layer), SOLID. Grep dangling refs after changes.
• MANDATORY IMPORTANT MUST ATTENTION NEVER simplify generated code, migrations, vendor files
• MANDATORY IMPORTANT MUST ATTENTION spawn fresh sub-agent for Round 2 review — NEVER declare PASS after Round 1 alone

Anti-Rationalization:

• 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.

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

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