five-s-auditor

name	five-s-auditor
description	5S workplace organization audit skill with scoring, photo documentation, and sustainability tracking.
allowed-tools	Bash(*) Read Write Edit Glob Grep WebFetch
metadata	{"author":"babysitter-sdk","version":"1.0.0","category":"lean-manufacturing","backlog-id":"SK-IE-012"}
graph	{"domains":["domain:industrial-engineering"],"skillAreas":["skill-area:statistical-analysis","skill-area:organizational-design","skill-area:data-analysis"],"roles":["role:operations-analyst","role:research-engineer"]}

five-s-auditor

You are five-s-auditor - a specialized skill for conducting 5S workplace organization audits with comprehensive scoring and tracking.

Overview

This skill enables AI-powered 5S auditing including:

• Sort (Seiri) red tag analysis
• Set in Order (Seiton) layout optimization scoring
• Shine (Seiso) cleanliness inspection
• Standardize (Seiketsu) visual management assessment
• Sustain (Shitsuke) audit scheduling
• Photo documentation and comparison
• Scoring trend analysis
• Action item tracking

Prerequisites

• 5S audit checklists
• Camera for photo documentation
• Understanding of 5S principles

Capabilities

1. 5S Audit Checklist

from dataclasses import dataclass
from typing import List, Optional
from enum import Enum
import datetime

class Rating(Enum):
    POOR = 1
    FAIR = 2
    GOOD = 3
    EXCELLENT = 4
    WORLD_CLASS = 5

@dataclass
class AuditQuestion:
    category: str  # S1-S5
    question: str
    rating: Optional[Rating] = None
    notes: str = ""
    photo_reference: str = ""
    action_required: bool = False

class FiveSAudit:
    """
    Complete 5S audit structure
    """
    def __init__(self, area_name: str, auditor: str):
        self.area_name = area_name
        self.auditor = auditor
        self.date = datetime.datetime.now()
        self.questions = self._initialize_questions()

    def _initialize_questions(self):
        return {
            "S1_Sort": [
                AuditQuestion(, ),
                AuditQuestion(, ),
                AuditQuestion(, ),
                AuditQuestion(, ),
                AuditQuestion(, ),
            ],
            : [
                AuditQuestion(, ),
                AuditQuestion(, ),
                AuditQuestion(, ),
                AuditQuestion(, ),
                AuditQuestion(, ),
            ],
            : [
                AuditQuestion(, ),
                AuditQuestion(, ),
                AuditQuestion(, ),
                AuditQuestion(, ),
                AuditQuestion(, ),
            ],
            : [
                AuditQuestion(, ),
                AuditQuestion(, ),
                AuditQuestion(, ),
                AuditQuestion(, ),
                AuditQuestion(, ),
            ],
            : [
                AuditQuestion(, ),
                AuditQuestion(, ),
                AuditQuestion(, ),
                AuditQuestion(, ),
                AuditQuestion(, ),
            ]
        }

     ():
        .questions[category][index].rating = rating
        .questions[category][index].notes = notes
        .questions[category][index].photo_reference = photo
         rating.value <= :
            .questions[category][index].action_required = 

2. Scoring and Analysis

def calculate_scores(audit: FiveSAudit):
    """
    Calculate 5S scores by category and overall
    """
    scores = {}

    for category, questions in audit.questions.items():
        rated = [q for q in questions if q.rating is not None]
        if rated:
            avg_score = sum(q.rating.value for q in rated) / len(rated)
            max_score = 5 * len(questions)
            actual_score = sum(q.rating.value for q in rated)

            scores[category] = {
                "average": round(avg_score, 2),
                "percentage": round(actual_score / max_score * 100, 1),
                "questions_rated": len(rated),
                "total_questions": len(questions),
                "action_items": sum(1 for q in questions if q.action_required)
            }

    # Overall score
    all_ratings = [q.rating.value for cat in audit.questions.values()
                   for q in cat if q.rating]
    if all_ratings:
        scores[] = {
            : ((all_ratings) / (all_ratings), ),
            : ((all_ratings) / ( * (all_ratings)) * , ),
            : get_grade((all_ratings) / (all_ratings))
        }

     scores

 ():
     avg_score >= :
         
     avg_score >= :
         
     avg_score >= :
         
     avg_score >= :
         
    :
         

3. Red Tag Analysis (Sort)

@dataclass
class RedTag:
    item_description: str
    location: str
    category: str  # tools, materials, equipment, documents, other
    condition: str  # good, damaged, obsolete
    last_used: Optional[datetime.date]
    disposition: str  # keep, relocate, dispose, sell
    value_estimate: float
    responsible_person: str
    decision_date: Optional[datetime.date] = None
    action_taken: str = ""

class RedTagTracking:
    """
    Track red-tagged items during Sort phase
    """
    def __init__(self, area_name: str):
        self.area_name = area_name
        self.tags: List[RedTag] = []
        self.start_date = datetime.date.today()

    def add_tag(self, tag: RedTag):
        self.tags.append(tag)

    def summary(self):
        dispositions = {}
        for tag in self.tags:
            dispositions[tag.disposition] = dispositions.get(tag.disposition, 0) + 1

        return {
            "total_items": len(self.tags),
            : dispositions,
            : (t.value_estimate  t  .tags),
            : (  t  .tags   t.decision_date),
            : ._by_category()
        }

     ():
        categories = {}
         tag  .tags:
             tag.category   categories:
                categories[tag.category] = []
            categories[tag.category].append(tag.item_description)
         categories

4. Visual Management Assessment

def assess_visual_management(area_observations):
    """
    Evaluate visual management maturity
    """
    criteria = {
        "floor_markings": {
            "present": False,
            "compliant": False,
            "comments": ""
        },
        "tool_boards": {
            "present": False,
            "shadows_complete": False,
            "all_tools_present": False,
            "comments": ""
        },
        "labeling": {
            "locations_labeled": False,
            "consistent_format": False,
            "legible": False,
            "comments": ""
        },
        "status_boards": {
            "production_status": False,
            "quality_metrics": False,
            "safety_info": False,
            "updated_regularly": False,
            "comments": ""
        },
        "abnormality_signals": {
            "andon_present": False,
            "clear_escalation": False,
            "comments": ""
        }
    }

    
    score = 
    max_score = 

     category, items  criteria.items():
         key, value  items.items():
             key != :
                max_score += 
                 area_observations.get(category, {}).get(key):
                    score += 

     {
        : criteria,
        : score,
        : max_score,
        : (score / max_score * , )  max_score >   ,
        : get_visual_maturity_level(score / max_score  max_score >   )
    }

 ():
     ratio >= :
         
     ratio >= :
         
     ratio >= :
         
     ratio >= :
         
    :
         

5. Trend Analysis

def analyze_audit_trends(audit_history: List[dict]):
    """
    Analyze 5S scores over time
    """
    if len(audit_history) < 2:
        return {"message": "Need at least 2 audits for trend analysis"}

    # Sort by date
    sorted_audits = sorted(audit_history, key=lambda x: x['date'])

    trends = {
        "overall": [],
        "S1_Sort": [],
        "S2_SetInOrder": [],
        "S3_Shine": [],
        "S4_Standardize": [],
        "S5_Sustain": []
    }

    for audit in sorted_audits:
        trends["overall"].append({
            "date": audit['date'],
            "score": audit['scores']['overall']['percentage']
        })
        for category in ["S1_Sort", "S2_SetInOrder", "S3_Shine",
                        "S4_Standardize", "S5_Sustain"]:
            if category in audit['scores']:
                trends[category].append({
                    "date": audit['date'],
                    "score": audit['scores'][category]['percentage']
                })

    
    analysis = {}
     category, data  trends.items():
         (data) >= :
            recent = data[-:]  (data) >=   data
            first_score = recent[][]
            last_score = recent[-][]
            change = last_score - first_score

            analysis[category] = {
                : last_score,
                : (change, ),
                :   change >     change < -  ,
                : (data)
            }

     analysis

6. Action Item Tracking

@dataclass
class ActionItem:
    description: str
    category: str  # S1-S5
    priority: str  # high, medium, low
    responsible: str
    due_date: datetime.date
    status: str = "open"  # open, in_progress, completed, overdue
    completion_date: Optional[datetime.date] = None
    notes: str = ""

class ActionItemTracker:
    """
    Track 5S improvement actions
    """
    def __init__(self):
        self.items: List[ActionItem] = []

    def add_from_audit(self, audit: FiveSAudit):
        """Generate action items from audit findings"""
        for category, questions in audit.questions.items():
            for q in questions:
                if q.action_required:
                    self.items.append(ActionItem(
                        description=f"Address: {q.question} - {q.notes}",
                        category=category,
                        priority="high" if q.rating.value == 1 else "medium",
                        responsible="TBD",
                        due_date=datetime.date.today() + datetime.timedelta(days=14)
                    ))

     ():
        statuses = {: , : , : , : }

         item  .items:
             item.status ==   item.due_date < datetime.date.today():
                item.status = 
            statuses[item.status] += 

         {
            : (.items),
            : statuses,
            : statuses[] / (.items) *   .items  ,
            : statuses[]
        }

Process Integration

This skill integrates with the following processes:

• 5s-workplace-organization-implementation.js
• kaizen-event-facilitation.js
• standard-work-development.js

Output Format

{
  "audit_info": {
    "area": "Assembly Line 3",
    "auditor": "John Smith",
    "date": "2024-01-15"
  },
  "scores": {
    "S1_Sort": {"percentage": 80, "grade": "Good"},
    "S2_SetInOrder": {"percentage": 85, "grade": "Good"},
    "S3_Shine": {"percentage": 70, "grade": "Fair"},
    "S4_Standardize": {   
        
        
  
   
   
     
     
     
  
   

Best Practices

1. Regular audits - Weekly or bi-weekly consistency
2. Rotate auditors - Fresh eyes find more
3. Take photos - Visual evidence of progress
4. Follow up on actions - Close the loop
5. Celebrate wins - Recognize improvements
6. Post results - Transparency drives improvement

Constraints

• Audits should be constructive, not punitive
• Include area workers in the process
• Document all findings objectively
• Track trends over time