vibeeval/vibecosystem/skills/ai-slop-cleaner/SKILL.md
ai-slop-cleaner
Post-implementation cleanup that removes AI-generated bloat while preserving functionality. Runs pass-by-pass with test verification after each pass. Activate after kraken/spark complete a feature, or when a codebase needs hygiene work.
- Source repository stars
- 528
- Declared platforms
- 0
- Static risk flags
- 0
- Last source update
- 2026-08-08
- Source checked
- 2026-08-25
Decision brief
What it does: where it fits
AI code generation produces working code. It also produces unnecessary code alongside it. This skill removes the unnecessary parts while keeping everything that matters.
Not for
- Tasks that require unconfirmed production actions or broad system permissions.
- Environments where the pinned source and install steps cannot be inspected.
Compatibility matrix
Platform support, with evidence labels
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
Inspect first. Install second.
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/vibeeval/vibecosystem --skill "skills/ai-slop-cleaner"Inspect the Agent Skill "ai-slop-cleaner" from https://github.com/vibeeval/vibecosystem/blob/3b763b1fb288f57bfa3cce76ef18184b96461a78/skills/ai-slop-cleaner/SKILL.md at commit 3b763b1fb288f57bfa3cce76ef18184b96461a78. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
What the source asks the agent to do
- 01
Regression-Safe Workflow (Non-Negotiable)
Never batch multiple pass categories together. If combined changes break a test, you cannot know which change caused it.
Never batch multiple pass categories together. If combined changes break a test, you cannot know which change caused it. - 02
What Is "AI Slop"?
AI slop is code that: - Works, but shouldn't exist - Adds complexity without adding value - Was clearly generated to pad a response rather than solve a problem - Suggests the author wasn't thinking, just generating
Works, but shouldn't existAdds complexity without adding valueWas clearly generated to pad a response rather than solve a problem - 03
The Prime Directive
Tests are sacred. Never clean test files.
Tests are sacred. Never clean test files.Tests exist to protect behavior. Any cleanup that breaks a test reveals that the "slop" was actually load-bearing. That is good information. The test wins. - 04
The 7 Cleaning Passes
What to remove: - Import statements where the imported name never appears in the file body - Variables declared with let/const/var that are never read after assignment - Function parameters that are never referenced inside the function body (TypeScript: prefix with )
Import statements where the imported name never appears in the file bodyVariables declared with let/const/var that are never read after assignmentFunction parameters that are never referenced inside the function body (TypeScript: prefix with ) - 05
Pass 1: Dead Imports and Unused Variables
What to remove: - Import statements where the imported name never appears in the file body - Variables declared with let/const/var that are never read after assignment - Function parameters that are never referenced inside the function body (TypeScript: prefix with )
Import statements where the imported name never appears in the file bodyVariables declared with let/const/var that are never read after assignmentFunction parameters that are never referenced inside the function body (TypeScript: prefix with )
Permission review
Static risk signals and limitations
No configured static risk pattern was detected
This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.
Evidence record
Why each signal appears
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 95/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 528 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Provenance and original SKILL.md
- Repository
- vibeeval/vibecosystem
- Skill path
- skills/ai-slop-cleaner/SKILL.md
- Commit
- 3b763b1fb288f57bfa3cce76ef18184b96461a78
- License
- MIT
- Collected
- 2026-08-25
- Default branch
- main
View the original SKILL.md
AI Slop Cleaner
AI code generation produces working code. It also produces unnecessary code alongside it. This skill removes the unnecessary parts while keeping everything that matters.
What Is "AI Slop"?
AI slop is code that:
- Works, but shouldn't exist
- Adds complexity without adding value
- Was clearly generated to pad a response rather than solve a problem
- Suggests the author wasn't thinking, just generating
Common slop categories and their signals:
| Category | Signal |
|---|---|
| Dead imports | Imported but never referenced in the file |
| Unused variables | Declared, never read |
| Commented-out code | Blocks of // old code or /* removed */ |
| Debug remnants | console.log, print(), debugger, fmt.Println |
| Obvious comments | // increment counter above count++ |
| Redundant JSDoc | @param name - the name above name: string |
| Premature abstractions | A factory that creates exactly one thing |
| One-use helpers | Private function called exactly once, trivially inlinable |
| Overly generic types | <T extends object> when T is always User |
| Over-parameterized | fn(a, b, c, d, e) where 4 params never vary |
| Unreachable branches | if (false) or if (isLoggedIn && !isLoggedIn) |
| Speculative features | Code paths for requirements that don't exist |
| Copy-paste duplication | Two blocks identical except one variable name |
| Placeholder remnants | TODO: implement, lorem ipsum, example data in prod |
The Prime Directive
Tests are sacred. Never clean test files.
Tests exist to protect behavior. Any cleanup that breaks a test reveals that the "slop" was actually load-bearing. That is good information. The test wins.
Regression-Safe Workflow (Non-Negotiable)
BEFORE ANYTHING: Run full test suite → all tests must pass (baseline)
FOR EACH PASS:
1. Identify targets for this pass category
2. Apply cleanup
3. Run tests
4. If tests pass: keep cleanup, continue
5. If tests fail: git checkout -- . (revert), skip this pass category
6. Log what was reverted and why
AFTER ALL PASSES: Run full test suite → confirm all tests still pass
Report: lines removed, files touched, passes skipped, reason for each skip
Never batch multiple pass categories together. If combined changes break a test, you cannot know which change caused it.
The 7 Cleaning Passes
Pass 1: Dead Imports and Unused Variables
Risk: Very Low
What to remove:
- Import statements where the imported name never appears in the file body
- Variables declared with
let/const/varthat are never read after assignment - Function parameters that are never referenced inside the function body (TypeScript: prefix with
_)
Before:
import { useState, useEffect, useCallback, useMemo } from 'react'
import { formatDate } from '@/lib/utils'
import { ApiClient } from '@/lib/api'
export function UserCard({ user }) {
const [count, setCount] = useState(0)
const formatted = formatDate(user.createdAt)
return <div>{user.name}</div>
}
After:
import { useState } from 'react'
import { formatDate } from '@/lib/utils'
export function UserCard({ user }) {
const [count, setCount] = useState(0)
const formatted = formatDate(user.createdAt)
return <div>{user.name}</div>
}
Note: count, setCount, and formatted are still present because they may be used elsewhere in a larger component. Pass 1 only removes imports.
Pass 2: Commented-Out Code and Debug Statements
Risk: Very Low
What to remove:
- Any block of commented-out code that is not an active TODO or architectural note
console.log,console.debug,console.warn(unless it is a legitimate error logger)debuggerstatementsprint()in Python when not serving as actual program outputfmt.Printlnin Go debug instrumentation
Before:
async function processOrder(orderId: string) {
console.log('processing order', orderId)
const order = await db.orders.findById(orderId)
// const cached = await cache.get(orderId)
// if (cached) return cached
console.log('order fetched:', order)
const result = await payments.charge(order)
// TODO: add retry logic here
// console.log('charge result', result)
return result
}
After:
async function processOrder(orderId: string) {
const order = await db.orders.findById(orderId)
const result = await payments.charge(order)
// TODO: add retry logic here
return result
}
Rule: // TODO: comments are preserved. They are documentation of known gaps, not slop.
Pass 3: Obvious Comments and Redundant Documentation
Risk: Low
What to remove:
- Comments that restate the code in plain English without adding context
- JSDoc
@paramblocks that just repeat the parameter name and type (TypeScript already says this) - Section dividers that add no structure (
// ===== COMPONENT =====) - End-of-block comments (
} // end if,} // end for)
Before:
/**
* Gets a user by ID.
* @param id - the user ID
* @param db - the database instance
* @returns the user object
*/
async function getUserById(id: string, db: Database): Promise<User> {
// Query the database for the user
const user = await db.users.findById(id)
// Return the user
return user
} // end getUserById
After:
async function getUserById(id: string, db: Database): Promise<User> {
return db.users.findById(id)
}
Keep comments that explain WHY (business rules, performance choices, known gotchas). Remove comments that explain WHAT (the code already says what).
Pass 4: Dead Code (Unreachable Branches)
Risk: Medium — Run tests immediately after
What to remove:
- Conditions that are always true or always false
- Code after unconditional
return,throw, orbreak - Else branches of conditions that always throw in the if block
Before:
function getStatus(user: User): string {
if (user.role === 'admin' || user.role === 'admin') {
return 'ADMIN'
}
if (user.isActive) {
return 'ACTIVE'
} else {
return 'INACTIVE'
}
// This never runs
return 'UNKNOWN'
}
After:
function getStatus(user: User): string {
if (user.role === 'admin') {
return 'ADMIN'
}
return user.isActive ? 'ACTIVE' : 'INACTIVE'
}
Do not remove branches that look unreachable but depend on runtime data you cannot verify statically. When uncertain, leave it.
Pass 5: Premature Abstractions (Inline One-Use Helpers)
Risk: Medium — Run tests immediately after
What to inline:
- Private/internal functions called exactly once
- Wrapper functions that add no logic (just forward all arguments)
- Intermediate variables assigned once and used once on the next line
Before:
function formatUserDisplayName(user: User): string {
return `${user.firstName} ${user.lastName}`.trim()
}
function renderUserCard(user: User) {
const displayName = formatUserDisplayName(user)
return `<div class="card">${displayName}</div>`
}
After (if formatUserDisplayName is only called from renderUserCard):
function renderUserCard(user: User) {
const displayName = `${user.firstName} ${user.lastName}`.trim()
return `<div class="card">${displayName}</div>`
}
Do NOT inline if:
- The function is exported (public API)
- The function is called from more than one place
- The function name serves as meaningful documentation of intent
- The function contains error handling that would add visual noise when inlined
Pass 6: Duplication Consolidation
Risk: Medium-High — Run tests immediately after each consolidation
What to consolidate:
- Two or more blocks with identical structure and only one variable difference
- Repeated conditional checks that could be extracted to a guard function
- Multiple switch/if-else blocks with the same cases in different files
Before:
// In UserService
async function getActiveUsers() {
const users = await db.query(
'SELECT * FROM users WHERE status = $1 AND deleted_at IS NULL',
['active']
)
return users.rows
}
// In AdminService (same file or different file)
async function getActiveAdmins() {
const admins = await db.query(
'SELECT * FROM users WHERE status = $1 AND deleted_at IS NULL AND role = $2',
['active', 'admin']
)
return admins.rows
}
After:
async function getActiveUsers(role?: string) {
const params: unknown[] = ['active']
let sql = 'SELECT * FROM users WHERE status = $1 AND deleted_at IS NULL'
if (role) {
sql += ' AND role = $2'
params.push(role)
}
const result = await db.query(sql, params)
return result.rows
}
Be careful: consolidation that requires complex parameterization may make code harder to understand. If the consolidated version is more complex than the two originals, leave them separate.
Pass 7: Over-Engineering Simplification
Risk: High — High scrutiny, run tests after every individual change
What to simplify:
- Factory pattern used to create exactly one concrete type
- Strategy pattern with exactly one strategy
- Abstract base class with exactly one implementation
- Generic type parameter constrained so tightly it could be a concrete type
Before:
interface DataProcessor<T extends BaseData> {
process(data: T): ProcessedData<T>
validate(data: T): ValidationResult
}
class UserDataProcessorFactory {
create(): DataProcessor<UserData> {
return new UserDataProcessor()
}
}
class UserDataProcessor implements DataProcessor<UserData> {
process(data: UserData): ProcessedData<UserData> {
return { ...data, processed: true }
}
validate(data: UserData): ValidationResult {
return { valid: !!data.id }
}
}
After (if only UserData ever flows through this):
function processUserData(data: UserData) {
if (!data.id) throw new Error('Invalid user data: missing id')
return { ...data, processed: true }
}
Rule for Pass 7: If you need more than 2 minutes to understand why an abstraction exists, and there is only one concrete case, remove the abstraction. If you find yourself unsure whether it is load-bearing, leave it. Pass 7 is optional.
What Is Never Cleaned
| Target | Reason |
|---|---|
Test files (*.test.*, *.spec.*, __tests__/) | Tests are sacred |
| Public API signatures | Breaks callers |
| Error handling at system boundaries (API routes, top-level handlers) | Defense-in-depth |
| Comments explaining regulatory/compliance requirements | Legal context |
| Feature flags | May be toggled at runtime |
Anything marked // KEEP or // intentional | Explicit author decision |
.slopignore File
Place at project root to exclude paths:
# .slopignore
src/legacy/ # Old code being migrated, don't touch
src/generated/ # Auto-generated, cleaned by generator
vendor/ # Third-party code
Metrics Report
After all passes complete, output:
AI Slop Cleaner Report
======================
Files touched: 12
Lines removed: 147
Lines remaining: 1,843
Reduction: 7.4%
Pass results:
Pass 1 (Dead imports): DONE — 23 lines removed
Pass 2 (Debug code): DONE — 18 lines removed
Pass 3 (Obvious comments): DONE — 41 lines removed
Pass 4 (Dead code): DONE — 12 lines removed
Pass 5 (One-use helpers): DONE — 31 lines removed
Pass 6 (Duplication): SKIPPED — test failed after consolidation (UserService)
Pass 7 (Over-engineering): DONE — 22 lines removed
Skipped details:
Pass 6 reverted: UserService query consolidation broke getUsersByStatus test.
Root cause: test was asserting on the exact SQL string. Left original.
Test status: ALL PASSING (127/127)
Integration with refactor-cleaner Agent
AI slop cleaner runs at the code level (syntactic cleanup). The refactor-cleaner agent runs at the architecture level (structural refactoring). Run this skill first, then refactor-cleaner if structural improvement is needed.
Order:
1. ai-slop-cleaner (remove the noise)
2. code-reviewer (verify quality after cleanup)
3. refactor-cleaner (structural improvements if needed)
4. verifier (final gate)
Automatic Trigger
This skill is automatically triggered after:
- kraken agent completes a feature implementation
- spark agent completes a fix
- Any agent produces more than 200 new lines of code
The trigger runs Pass 1 and Pass 2 only by default (very low risk). Passes 3-7 require explicit activation or a /clean command.
Remember: The goal is not minimum lines of code. The goal is maximum clarity per line. If removing something makes the code harder to understand, put it back.
Frequently asked questions
What to verify before installation and use
What does the ai-slop-cleaner source document cover?
AI code generation produces working code. It also produces unnecessary code alongside it. This skill removes the unnecessary parts while keeping everything that matters.
How do I install ai-slop-cleaner?
The source record exposes this install command: npx skills add https://github.com/vibeeval/vibecosystem --skill "skills/ai-slop-cleaner". Inspect the command and pinned source before running it.
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