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Expert Electron application architecture skill for IPC design, main/renderer/preload boundaries, security hardening, performance optimization, packaging strategy, native integration, and cross-platform desktop development. Use when reviewing or designing Electron apps, planning migrations, auditing architecture risks, choosing IPC patterns, diagnosing startup or memory issues, or coordinating related Electron skills.
Generates DrawIO XML diagrams for Amazon Web Services architectures from text descriptions or images. Analyzes existing .drawio files to extract AWS components. Use for AWS architecture diagrams, cloud infrastructure documentation, or when converting AWS diagram images to editable DrawIO format.
Generates DrawIO XML diagrams for Google Cloud Platform architectures from text descriptions or images. Analyzes existing .drawio files to extract GCP components. Use for GCP architecture diagrams, cloud infrastructure documentation, or when converting GCP diagram images to editable DrawIO format.
基于 SOC 职业分类
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| 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"} |
You are five-s-auditor - a specialized skill for conducting 5S workplace organization audits with comprehensive scoring and tracking.
This skill enables AI-powered 5S auditing including:
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("S1", "Are there any unnecessary items in the work area?"),
AuditQuestion("S1", "Have all items been evaluated with red tags?"),
AuditQuestion("S1", "Is there a clear process for disposing of unneeded items?"),
AuditQuestion("S1", "Are personal items stored appropriately?"),
AuditQuestion("S1", "Are there any broken or damaged items present?"),
],
"S2_SetInOrder": [
AuditQuestion("S2", "Do all items have a designated location?"),
AuditQuestion("S2", "Are locations clearly marked/labeled?"),
AuditQuestion("S2", "Are frequently used items easily accessible?"),
AuditQuestion("S2", "Is there a clear organization system (color coding, etc.)?"),
AuditQuestion("S2", "Can anyone find items within 30 seconds?"),
],
"S3_Shine": [
AuditQuestion("S3", "Is the floor clean and free of debris?"),
AuditQuestion("S3", "Is equipment clean and well-maintained?"),
AuditQuestion("S3", "Are cleaning supplies readily available?"),
AuditQuestion("S3", "Is there a cleaning schedule posted and followed?"),
AuditQuestion("S3", "Are potential contamination sources identified?"),
],
"S4_Standardize": [
AuditQuestion("S4", "Are visual controls in place (floor markings, signs)?"),
AuditQuestion("S4", "Are standard procedures documented and posted?"),
AuditQuestion("S4", "Is there a visual management board?"),
AuditQuestion("S4", "Are abnormalities easy to identify?"),
AuditQuestion("S4", "Are standards consistent across similar areas?"),
],
"S5_Sustain": [
AuditQuestion("S5", "Are 5S audits conducted regularly?"),
AuditQuestion("S5", "Is there management involvement/support?"),
AuditQuestion("S5", "Are improvement suggestions encouraged?"),
AuditQuestion("S5", "Are previous action items completed?"),
AuditQuestion("S5", "Is 5S part of daily routine?"),
]
}
def rate_question(self, category: str, index: int, rating: Rating,
notes: str = "", photo: str = ""):
self.questions[category][index].rating = rating
self.questions[category][index].notes = notes
self.questions[category][index].photo_reference = photo
if rating.value <= 2:
self.questions[category][index].action_required = True
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 >= :
:
@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
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 >= :
:
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
@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[]
}
This skill integrates with the following processes:
5s-workplace-organization-implementation.jskaizen-event-facilitation.jsstandard-work-development.js{
"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": {