name	cleanup
description	Project organization expert - analyzes folder state, detects redundancy, moves files to proper locations, consolidates duplicate content, appends to accumulator files, removes obsolete content, and generates detailed operation reports. Maintains project structure integrity.
version	1.1.0

GabeDA Cleanup & Organization Expert

Purpose

This skill analyzes and organizes project folders to maintain clean, well-structured codebases. It understands project conventions, identifies redundancy, consolidates accumulator files, and removes obsolete content.

Key Capabilities:

Analyze current folder/project state
Detect redundant and duplicate content across files ⭐ NEW
Suggest document consolidation and merging ⭐ NEW
Move files to proper locations per project conventions
Append content to accumulator/living documents
Identify and remove obsolete files
Generate detailed operation and merge suggestion reports

When to Invoke

Use this skill when:

Project has accumulated duplicate/scattered files
Multiple files contain redundant or overlapping content ⭐ NEW
Need suggestions for document consolidation/merging ⭐ NEW
Files need reorganization per documentation standards
Content should be consolidated into living documents
Obsolete files need identification and removal
Need audit trail of file operations

Input required: Path(s) to folders needing cleanup

Workflow

1. Analyze Current State

Understand project structure:

Read project documentation standards (CLAUDE.md, DOCUMENTATION_STANDARD.md)
Identify living documents (10 accumulators in ai/ and docs/)
Map current file locations and relationships
Detect redundancy patterns

Generate state report:

Total files by type/category
Misplaced files (wrong folder)
Duplicate/redundant content
Accumulator opportunities (content that should be appended)
Obsolete file candidates

2. Detect Redundancy (⭐ NEW)

Analyze files for redundant content:

Content Similarity Analysis:

Compare file contents pairwise
Calculate similarity scores (0-100%)
Identify duplicate/near-duplicate clusters
Group files by content similarity

Pattern Recognition:

Detect versioned files (file_v1.md, file_v2.md, file_final.md)
Detect dated files (notes_2025_10.md, notes_2025_11.md)
Detect topic variants (auth.md, authentication.md, login_guide.md)

Topic Modeling:

Extract topics from file headings
Group files covering same topics
Identify fragmented information

Reference Analysis:

Count references to each file
Identify authoritative sources (heavily referenced)
Find orphan files (unreferenced duplicates)

Redundancy Scoring:

Assign redundancy score (0-10) to file groups
HIGH (9-10): Immediate consolidation recommended
MEDIUM (6-8): User review suggested
LOW (3-5): Optional optimization

Generate merge suggestions:

Present redundancy groups by priority
Propose consolidation strategies (MERGE/CONSOLIDATE/HIERARCHICAL/APPEND)
Estimate impact (file reduction, clarity improvement)
Request user approval before proceeding

Reference: cleanup/references/redundancy_detection.md

Template: cleanup/assets/templates/merge_suggestion_template.md

3. Categorize Files

Decision tree for each file:

FILE → Is it a living document?
       ├─ YES → Check if properly named/located
       │        ├─ YES → Skip (already correct)
       │        └─ NO → Flag for rename/move
       │
       └─ NO → Should content go into living doc?
               ├─ YES → Flag for append + delete
               │
               └─ NO → Is file obsolete?
                       ├─ YES → Flag for deletion
                       └─ NO → Is file in wrong folder?
                               ├─ YES → Flag for move
                               └─ NO → Skip (correct)

Reference: cleanup/references/file_categorization_rules.md

4. Plan Operations

Group operations by type:

MERGE - Consolidate redundant files (⭐ NEW)
MOVE - Files to relocate (with destination)
APPEND - Content to merge into living docs
DELETE - Obsolete files to remove
RENAME - Files needing name standardization

Safety checks:

Verify destinations exist
Check for overwrite conflicts
Validate accumulator file format compatibility
Confirm deletion safety (no external references)
Ensure unique content preserved during merges (⭐ NEW)

5. Execute with User Approval

Present operation plan:

Show all proposed operations in clear table format
Highlight potential risks (overwrites, deletions)
Explain rationale for each operation

Request approval:

CRITICAL: NEVER execute operations without explicit user approval
User reviews plan and confirms: "proceed", "skip deletions", "cancel", etc.

Execute approved operations:

Perform operations in safe order: MERGE → MOVE → APPEND → DELETE
Log each operation with timestamp
Handle errors gracefully (report, don't abort entire batch)

6. Generate Report

Create operation report using template: cleanup/assets/templates/cleanup_report_template.md

Report sections:

Summary: Total operations by type, files affected
Detailed log: Each operation with source/destination/timestamp
Errors: Any failures encountered
State comparison: Before/after folder structure
Recommendations: Further cleanup opportunities

Save report: cleanup_report_YYYYMMDD_HHMM.md in project root or user-specified location

Living Documents (10 Accumulators)

These files accumulate content - APPEND, don't replace:

ai/ Folder (AI Skill Accumulators)

ai/CHANGELOG.md - All code changes
ai/ISSUES.md - Bug fixes and resolutions
ai/PROJECT_STATUS.md - Sprint status and metrics
ai/FEATURE_IMPLEMENTATIONS.md - New features added
ai/TESTING_RESULTS.md - Test execution results
ai/SKILLS_MANAGEMENT.md - AI skills evolution
ai/testing/TEST_MANIFEST.md - Complete test catalog

docs/ Folder (Human-Readable)

ai/architect/ARCHITECTURE_DECISIONS.md - Design decisions (ADRs)
ai/guides/NOTEBOOK_IMPROVEMENTS.md - Notebook refactoring log
ai/planning/FUTURE_ENHANCEMENTS.md - Future TODOs

Reference: cleanup/references/accumulator_patterns.md

File Organization Rules

Standard locations per DOCUMENTATION_STANDARD.md:

Content Type	Proper Location	Examples
AI skill context	`ai/[skill-name]/`	feature_implementation_guide.md
AI conventions	`ai/conventions/`	constants.md, context_reuse.md
AI specs	`ai/specs/`	Technical specifications
AI standards	`ai/standards/`	8-metric evaluation standards
Human guides	`docs/guides/`	TESTING.md, COLUMN_SCHEMA_USAGE.md
Architecture	`docs/architecture/`	ARCHITECTURE_DECISIONS.md
Business docs	`docs/business/`	User personas, use cases
Test files	`test/[category]/`	unit/, integration/, validation/
Source code	`src/`	Core application code
Backend code	`backend/`	Django/DRF application
Frontend code	`frontend/`	React/Vite application

Reference: cleanup/references/folder_structure_guide.md

Obsolescence Detection

Files are likely obsolete if:

Contains "OLD", "BACKUP", "DEPRECATED" in name
Duplicates content in living documents
Replaced by newer versioned file
References outdated architecture (pre-refactoring)
Not referenced by any other file in project
Creation date > 90 days + no recent modifications

Manual review required before deletion:

Configuration files
Data files (CSVs, JSONs)
Files > 100 lines
Any file with "IMPORTANT" or "CRITICAL" markers

Reference: cleanup/references/obsolescence_criteria.md

Safety Guidelines

CRITICAL RULES:

ALWAYS get user approval before executing operations
NEVER delete without showing what will be deleted
NEVER overwrite without warning about conflicts
ALWAYS preserve original content (copy before transform)
ALWAYS generate operation report for audit trail

Dry-run mode: Present plan WITHOUT executing (default behavior)

Execution mode: Only after explicit user approval

Example Usage

User: "Clean up the ai/ folder"

Cleanup skill response:

## Analysis Complete: ai/ Folder

**Current State:**
- 156 files total
- 12 living documents (correct)
- 8 misplaced files detected
- 3 files should append to accumulators
- 5 obsolete files identified

**Proposed Operations:**

### MOVE (8 files)
1. ai/old_feature_spec.md → ai/specs/archive/
2. ai/test_results_20251020.md → ai/testing/archive/
   [... 6 more]

### APPEND (3 files)
1. ai/bug_fix_notes.md → ai/ISSUES.md (append content, then delete source)
2. ai/new_model_added.md → ai/FEATURE_IMPLEMENTATIONS.md
3. ai/sprint4_update.md → ai/PROJECT_STATUS.md

### DELETE (5 files)
1. ai/BACKUP_old_spec.md (obsolete - content in specs/)
2. ai/temp_notes.txt (temporary file, 92 days old)
   [... 3 more]

**Approve operations? (respond: 'proceed', 'skip deletions', 'cancel')**

More examples: cleanup/assets/examples/cleanup_scenarios.md

Example Usage with Redundancy Detection (⭐ NEW)

User: "Clean up the docs/ folder and suggest any document consolidation"

Cleanup skill response:

## Analysis Complete: docs/ Folder

**Current State:**
- 25 documentation files analyzed
- 3 living documents (correct)
- 1 README (correct)

**Redundancy Detection Results:**

### HIGH Redundancy (Score: 9/10)
**Group 1: Setup Guides (3 files)**
- setup_guide_v1.md (150 lines, modified 2025-09-15)
- setup_guide_v2.md (180 lines, modified 2025-10-01)
- setup_guide_final.md (200 lines, modified 2025-10-25) ← Most recent

Content similarity: 85% overlap
Suggestion: MERGE → Keep setup_guide_final.md, delete v1 and v2

### MEDIUM Redundancy (Score: 7/10)
**Group 2: Authentication Documentation (2 files)**
- api_authentication.md (120 lines, referenced by 3 files)
- auth_endpoints.md (95 lines, not referenced)

Content similarity: 70% overlap
Topic: Both cover authentication/login endpoints
Suggestion: CONSOLIDATE → Merge into single authentication.md

### Proposed Consolidation Operations:

**MERGE (Group 1):**
1. Keep: setup_guide_final.md
2. Extract unique content from v1 and v2 (if any)
3. Delete: setup_guide_v1.md, setup_guide_v2.md
4. Impact: 3 files → 1 file

**CONSOLIDATE (Group 2):**
1. Create: authentication.md
2. Merge content from both files
3. Update 3 references to point to new file
4. Delete source files
5. Impact: 2 files → 1 file

**Total Impact:**
- File reduction: 25 → 20 files (5 files consolidated, 20% reduction)
- Improved clarity: Single authoritative source for each topic
- Easier maintenance: Fewer files to keep updated

**Do you approve these consolidations?**
(respond: 'approve-all', 'approve group 1 only', 'modify', 'skip')

User response: "approve-all"

Cleanup skill executes consolidation + generates report with before/after comparison

Quality Standards

Cleanup operations must meet:

✅ Correctness (25%) - Files moved to proper locations per standards ✅ Safety (25%) - No data loss, user approval obtained ✅ Completeness (20%) - All redundancy/obsolescence addressed ✅ Auditability (20%) - Detailed operation report generated ✅ Reversibility (10%) - Operations can be undone if needed

Minimum score: 8.0/10 before executing operations.

Related Skills

Use other skills for:

executive - Decide project-level organization strategy
architect - Understand code architecture for proper categorization
business - Identify which documents are accumulator vs reference
insights - Organize notebook files and analysis outputs
marketing - Organize marketing assets and templates
ux-design - Organize design assets and wireframes

Bundled Resources

References:

file_categorization_rules.md - Decision logic for categorizing files
accumulator_patterns.md - How to append to living documents
folder_structure_guide.md - Standard project organization
obsolescence_criteria.md - Rules for identifying obsolete files
redundancy_detection.md - ⭐ NEW: Detect and consolidate redundant content

Templates:

cleanup_report_template.md - Standard operation report format
operation_plan_template.md - Pre-execution approval format
merge_suggestion_template.md - ⭐ NEW: Document merge suggestions

Examples:

cleanup_scenarios.md - Real cleanup examples with rationale

Version: 1.1.0 Last Updated: 2025-10-30 Skill Type: Project Organization & Redundancy Detection

cleanup

Install Skill

SKILL.md