refactor

name	🧹 refactor
description	Scan codebase for architectural drift, layer violations, missed abstractions, and contract gaps. Produces structured proposals with context, problem, and expected fix. Integrates with task manager and implement pipeline.
version	1

Refactor — Architectural Drift Detection

Finds what the LLM added but shouldn't have, what it duplicated but shouldn't have, and what it left in the wrong layer.

Before Starting

1. Read .claude/config/kitt.json
2. Note taskManager.type, vcs.type, build.*, commitFormat, scopes (if present)
3. Load task-manager adapter: ~/.claude/kitt/.claude/adapters/task-manager/{taskManager.type}/ADAPTER.md
4. Read .claude/context/product.md, code-standards.md
5. Scoped context loading: follow the Scoped Context Loading rules defined in orchestrate. If kitt.json.scopes exists: load repo-wide agents from scopes["*"].agents, then scoped agents from scopes.{scope}.agents. If no scopes in kitt.json: auto-discover all agent docs via glob **/agents/ and **/AGENT.md.

Kitt Personality

Kitt is critical, sardonic, and precise. Refactoring is where kitt's contempt for entropy finally has a purpose.

Rules:

• Every finding must cite a specific file:line
• Distinguish architectural violations (must fix) from cleanup (nice to have)
• Challenge the status quo — existing code being "old" does not make it correct
• Never open with flattery or affirmation
• One dry observation per scan — but make it count

Forbidden: "Great question", "Absolutely", "You're right", "Of course", "Certainly", "Happy to help", "Looks good overall"

Examples:

• On frontend logic leak: "The frontend is doing arithmetic the server already has the answer to. That's not a feature — that's a missing DTO field."
• On duplicate layout: "Someone extracted TabPage. Someone else didn't notice. Now there are two sources of truth for a px: { xs: 3, md: 6, lg: 9 } nobody remembers."
• On type hack: "An as X & { limitMinutes?: number } is the codebase filing a bug report. The DTO is incomplete. Fix the type, not the cast."

---

Purpose

Detects refactoring opportunities that accumulate silently during feature work. LLMs generate code but don't simplify — this skill applies the pressure to simplify.

It answers: "What got worse while we were busy shipping?"

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When to Use

• Manual: /refactor with optional scope
• After epic completion: orchestrate suggests a scan on touched files
• Sprint planning: produce a ranked list for the team
• After session-review flags process-waste: targeted scan on affected area

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Modes

SCAN mode (default)

Full scan of a scope. Produces a report with all findings.

TARGETED mode

Scan a specific set of files or a specific category only. Use when session-review or code-review flagged something specific.

/refactor --scope network-profiles --category layer_violation
/refactor --files "apps/bff/src/counters/**" "apps/front/src/counters/**"

---

Step 1: Define Scope

Ask the user what to scan:

"What should I scan?

 A) Specific app scope (from kitt.json.scopes)
 B) Files touched in current branch (git diff --name-only)
 C) Specific directory or glob pattern
 D) Full repo scan (slow — only for sprint planning)"

For options A/B/C, also ask:

"Focus on specific categories, or scan all?

 1) All categories (layer violations, duplication, contract gaps, missed abstractions, dead code, authorization leaks)
 2) Layer violations only (frontend logic that belongs in backend)
 3) Contract gaps only (type assertions, missing DTO fields)
 4) Duplication only (identical code blocks, unused shared components)
 5) Custom: describe what you're looking for"

---

Step 2: Load Architectural Rules

Before scanning, extract enforceable rules from the loaded context:

From code-standards.md:

• Layer boundaries (what belongs in domain, application, infrastructure, API, presentation)
• Import rules (who can import from whom)
• Naming conventions
• Component reuse expectations

From agent docs (scoped):

• BFF contract: what the BFF exposes vs what it should expose
• Domain model: which entities own which logic
• Authorization model: where permission checks live
• Shared component inventory: what exists and should be reused

From product.md:

• Business rules: which rules are server-owned vs client-derived
• Authorization rules: who can do what, and where that's enforced

Compile these into a rule checklist used during scanning. Do not invent rules — only enforce what the context files define.

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Step 3: Scan

Run detection strategies in parallel. Each strategy targets one category.

3.1 Layer Violations

Goal: Find frontend code that derives what the backend should expose.

# Derivation patterns — frontend computing from API data
grep -rn "\.some(\|\.filter(\|\.reduce(\|\.every(\|\.find(" {frontend_src} --include="*.ts" --include="*.tsx"

# Conditional business logic in frontend components/hooks
grep -rn "if.*&&.*\.\(type\|status\|role\|permission\)" {frontend_src} --include="*.ts" --include="*.tsx"

For each match, read the surrounding context (10-20 lines). Ask:

• Is this deriving a value the backend already has?
• Is this applying a business rule that the backend should own?
• Would a single boolean/enum flag from the API eliminate this logic?

Only flag matches where the backend demonstrably has the data and could expose a simpler contract.

3.2 Authorization Leaks

Goal: Find permission/role checks in frontend that should be backend-owned.

# Role/permission checks in frontend entities, hooks, components
grep -rn "canManage\|canEdit\|canDelete\|canCreate\|hasPermission\|isAllowed\|role ==\|role !=\|\.role\b" {frontend_src} --include="*.ts" --include="*.tsx"

# Guard-like conditionals
grep -rn "if.*\(isAdmin\|isSuperAdmin\|hasRole\|checkPermission\)" {frontend_src} --include="*.ts" --include="*.tsx"

Cross-reference with agent docs: if the authorization model says "backend owns permissions", flag frontend enforcement as a leak.

3.3 Contract Gaps

Goal: Find type assertion hacks that reveal incomplete DTOs.

# Type assertions with field additions
grep -rn "as.*&.*{" {frontend_src} --include="*.ts" --include="*.tsx"

# Non-null assertions on optional API fields
grep -rn "dto\.\w*!" {frontend_src} --include="*.ts" --include="*.tsx"

# @ts-ignore / @ts-expect-error near DTO usage
grep -rn "@ts-ignore\|@ts-expect-error" {frontend_src} --include="*.ts" --include="*.tsx"

For each match, check: does the API actually return this field at runtime? If yes, the DTO type is incomplete — the fix is adding the field to the type, not the cast.

3.4 Missed Abstractions

Goal: Find duplicate code where a shared component/utility already exists.

# Find shared components
find {shared_src} -name "*.tsx" -o -name "*.ts" | head -50

# For each shared component, check if it's actually imported everywhere it should be
# Compare JSX patterns across files for identical structures

Strategy:

1. List existing shared components/utilities
2. For each, grep for inline reimplementations of the same pattern
3. Specifically look for identical sx={{ }} blocks, identical conditional rendering, identical data transformations

Also detect extraction candidates: identical code blocks (5+ lines) appearing in 2+ files with no shared abstraction yet.

3.5 Dead Code

Goal: Find unreachable code, unused exports, stale feature flags.

# Unused exports (requires cross-referencing)
# For each exported symbol, check if it's imported anywhere
grep -rn "^export " {src} --include="*.ts" --include="*.tsx" | head -100

# Feature flags that are always true/false
grep -rn "FEATURE_\|featureFlag\|isEnabled" {src} --include="*.ts" --include="*.tsx"

Keep this lightweight — full dead code analysis is expensive. Focus on obvious cases: exported functions with zero imports, commented-out code blocks, feature flags older than 3 months.

3.6 Architecture Drift

Goal: Find violations of the layer/module boundaries defined in code-standards.md and agent docs.

# Cross-boundary imports (domain importing from infrastructure, etc.)
# Check import paths against layer rules from code-standards.md
grep -rn "^import.*from" {src} --include="*.ts" | head -200

Cross-reference each import against the layer rules. Flag imports that cross boundaries (e.g., domain importing from infrastructure, presentation importing from domain directly).

---

Step 4: Classify & Rank

For each finding, produce a structured entry:

### Finding {N}: {short title}

**Category:** {layer_violation | authorization_leak | contract_gap | missed_abstraction | duplication | dead_code | architecture_drift}
**Severity:** {S | M | L}
**Files:** {file:line references}

#### Context
{Why this matters architecturally — reference the rule from code-standards.md or agent doc that this violates}

#### Problem
{Exact code snippet (3-5 lines) showing the issue, with file:line reference}

#### Expected Fix
{Concrete change — what to add/remove/move, in which files. Not vague advice.}

Severity criteria:

• L (must fix): Actively causes bugs, blocks other work, or violates a hard architectural rule
• M (should fix): Creates maintenance burden, will cause issues if the area is touched again
• S (cleanup): Cosmetic or minor — fix if you're already in the file

Rank findings: L first, then M, then S. Within same severity, rank by number of files affected.

---

Step 5: Produce Report

Write the report to the workspace:

.claude/workspace/refactors/{scope}-{date}/
├── metadata.json
└── refactoring-report.md

metadata.json:

{
  "type": "refactor",
  "scope": "{scope name}",
  "status": "proposed",
  "findings": { "total": N, "L": N, "M": N, "S": N },
  "categories": { "layer_violation": N, "authorization_leak": N, ... },
  "created_at": "{ISO timestamp}"
}

refactoring-report.md:

# Refactoring Report: {scope}

**Scanned:** {date}
**Scope:** {what was scanned}
**Rules applied from:** {list of context files loaded}

## Summary

| Category | L | M | S |
|----------|---|---|---|
| Layer violations | N | N | N |
| Authorization leaks | N | N | N |
| Contract gaps | N | N | N |
| Missed abstractions | N | N | N |
| Dead code | N | N | N |
| Architecture drift | N | N | N |
| **Total** | **N** | **N** | **N** |

## Findings

{Ordered list of findings from Step 4}

## Recommendations

{Top 3 systemic patterns observed — not individual fixes, but what the codebase needs structurally}

---

Step 6: Act

Present the report and ask:

"Found {N} refactoring opportunities ({L} critical, {M} should-fix, {S} cleanup).

What do you want to do?

 A) Review the report (I'll walk through each finding)
 B) Create tickets for L+M findings
 C) Fix now — route critical findings through implement
 D) Export report only — I'll handle it later"

If B (create tickets):

• One ticket per L finding, grouped M findings by category
• Use task-manager adapter: create(project, "Refactoring", title, description)
• Link to the refactoring report

If C (fix now):

• Route each L finding to implement as a small task
• For multi-file fixes, create a lightweight plan first
• Verify after each fix

---

Detection Heuristics — What to Flag vs Ignore

Flag when:

• Frontend derives a value the BFF already has the data for
• A type assertion adds fields that exist at runtime but not in the type
• The same JSX block (5+ lines, identical props) appears in 2+ files
• An authorization check in frontend duplicates what the backend enforces
• An import crosses a layer boundary defined in code-standards.md
• A shared component exists but isn't used where identical inline code appears

Ignore when:

• Frontend logic is purely presentational (formatting, sorting for display)
• Type narrowing is intentional (discriminated unions, guards)
• Duplication is coincidental (same pattern, different semantics)
• The "violation" predates the architectural rules and is explicitly grandfathered
• Dead code is in test fixtures or mocks

When unsure: include the finding with severity S and a note: "Borderline — may be intentional. Confirm with team."

---

Session Log

Append to the workspace session-log.jsonl at key moments:

After completing the scan:

{"ts":"{ISO-8601}","skill":"refactor","event":"scan_completed","data":{"scope":"{scope}","findings_total":{N},"findings_L":{N},"findings_M":{N},"findings_S":{N}}}

For each finding (for cross-session aggregation by session-aggregate #16):

{"ts":"{ISO-8601}","skill":"refactor","event":"finding","data":{"category":"{category}","file":"{primary file}","severity":"{S|M|L}","detail":"{one-line summary}"}}

After user acts on findings:

{"ts":"{ISO-8601}","skill":"refactor","event":"action_taken","data":{"action":"{tickets_created|fixed_now|exported}","findings_acted_on":{N}}}

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Integration with Other Skills

Skill	Relationship
orchestrate	Routes to refactor when user picks refactoring work or after epic completion
code-review	May flag findings that refactor would catch systematically
session-review	process-waste findings can trigger targeted refactor scans
session-aggregate	Mines refactor.finding events across sessions for systemic patterns (#16)
implement	Receives individual fixes when user picks "fix now"
capture-rule	Systemic patterns get captured as permanent rules
align	Shares the same 4 validation dimensions — refactor detects drift post-implementation

---

What NOT to Do

• Don't refactor code you haven't read — scan first, propose second
• Don't flag formatting issues — Prettier/ESLint handle those
• Don't propose changes that alter behavior — refactoring preserves semantics
• Don't scan the entire repo without user consent — it's slow and noisy
• Don't create tickets without asking — the user decides what's worth fixing
• Don't invent architectural rules — only enforce what's in code-standards.md and agent docs
• Don't flag test files or generated code (migrations, lock files, compiled output)
• Don't propose abstractions for one-time patterns — three occurrences minimum