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Reference for querying the Atlas knowledge graph through its MCP tools — the SECONDARY enrichment/comparison layer that adds best-practice context to systems you have ALREADY scanned from your real sources (`az`, repos, dirs). Use when you need to look up nodes, edges, kinds, clusters, stats, or wiki pages in Atlas to compare against your real inventory. (atlas graph, query atlas, atlas mcp, search the graph, graph neighbors, atlas record, atlas kinds, enrichment layer)
Atlas turns your STATED NEED into a real systems atlas by SCANNING your actual sources (Azure via `az`, git repos, local dirs) and process/data mining them, THEN enriching against the Atlas knowledge graph. Use this skill when asked to inventory/map your real systems, scan your cloud + repos + directories, mine the real processes or data they contain, or collect their real constraints/gotchas. (atlas, scan my systems, inventory our azure account, map my repos, real systems atlas, process mining, data mining, collect nuances, system discovery)
This skill should be used when the user asks to "find skills in the wild", "assimilate popular workflows", "discover SKILL.md files in repos", "research external skills", "find workflow patterns", "survey the skill landscape", "what skills exist out there", or wants to investigate public repositories for extractable processes, babysitter plugins, and reusable procedural insights. Searches GitHub for SKILL.md files, classifies repos by archetype, and maintains structured research under docs/reference-repos/.
正在显示 SKILL.md
基于 SOC 职业分类
| name | smed-analyzer |
| description | Single Minute Exchange of Die analysis skill for changeover time reduction. |
| allowed-tools | Bash(*) Read Write Edit Glob Grep WebFetch |
| metadata | {"author":"babysitter-sdk","version":"1.0.0","category":"lean-manufacturing","backlog-id":"SK-IE-011"} |
| 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"]} |
You are smed-analyzer - a specialized skill for analyzing and reducing changeover times using the Single Minute Exchange of Die (SMED) methodology.
This skill enables AI-powered SMED analysis including:
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional
import datetime
class ActivityType(Enum):
INTERNAL = "internal" # Machine must be stopped
EXTERNAL = "external" # Can be done while running
@dataclass
class ChangeoverActivity:
id: int
description: str
start_time: float # seconds from changeover start
end_time: float
activity_type: ActivityType
operator: str
tools_required: List[str]
notes: Optional[str] = None
@property
def duration(self):
return self.end_time - self.start_time
class ChangeoverAnalysis:
"""
Record and analyze changeover activities
"""
def __init__(self, machine_name: str, from_product: str, to_product: str):
self.machine_name = machine_name
.from_product = from_product
.to_product = to_product
.activities: [ChangeoverActivity] = []
.timestamp = datetime.datetime.now()
():
activity = ChangeoverActivity(
=(.activities) + ,
description=description,
start_time=start,
end_time=end,
activity_type=activity_type,
operator=operator,
tools_required=tools [],
notes=notes
)
.activities.append(activity)
activity
():
internal = [a a .activities a.activity_type == ActivityType.INTERNAL]
external = [a a .activities a.activity_type == ActivityType.EXTERNAL]
{
: (a.end_time a .activities),
: (a.duration a internal),
: (a.duration a external),
: (.activities),
: (internal),
: (external)
}
def analyze_internal_external(activities):
"""
Identify activities that could be converted from internal to external
"""
conversion_opportunities = []
for activity in activities:
if activity.activity_type == ActivityType.INTERNAL:
# Check for conversion potential
potential = assess_conversion_potential(activity)
if potential['can_convert']:
conversion_opportunities.append({
"activity_id": activity.id,
"description": activity.description,
"current_duration": activity.duration,
"conversion_method": potential['method'],
"estimated_savings": potential['savings'],
"investment_required": potential['investment']
})
return conversion_opportunities
def assess_conversion_potential(activity):
"""
Assess if internal activity can become external
"""
# Keywords indicating conversion potential
prep_keywords = ['get', 'find', 'look for', 'search', 'locate', 'bring']
adjustment_keywords = ['adjust', 'set', 'calibrate', 'tune']
removal_keywords = ['remove', 'take off', 'disconnect']
desc_lower = activity.description.lower()
# Preparation activities can often be done externally
(kw desc_lower kw prep_keywords):
{
: ,
: ,
: activity.duration * ,
:
}
(kw desc_lower kw adjustment_keywords):
{
: ,
: ,
: activity.duration * ,
:
}
{: }
def analyze_parallel_opportunities(activities, available_operators):
"""
Identify activities that can be done in parallel
"""
# Group activities by time window
timeline = []
for activity in activities:
timeline.append({
'time': activity.start_time,
'type': 'start',
'activity': activity
})
timeline.append({
'time': activity.end_time,
'type': 'end',
'activity': activity
})
timeline.sort(key=lambda x: x['time'])
# Analyze operator utilization
parallel_opportunities = []
current_activities = []
for event in timeline:
if event['type'] == 'start':
current_activities.append(event['activity'])
else:
current_activities.remove(event['activity'])
# Check if operators are idle
active_operators = len(set(a.operator for a in current_activities))
idle_operators = available_operators - active_operators
if idle_operators > 0 and len(current_activities) > 0:
parallel_opportunities.append({
'time': event['time'],
'idle_operators': idle_operators,
'active_activities': [a.description a current_activities]
})
parallel_opportunities
():
assignments = {i: [] i (available_operators)}
operator_end_times = [] * available_operators
sorted_activities = (activities, key= a: a.start_time)
activity sorted_activities:
earliest_op = ((available_operators),
key= i: operator_end_times[i])
new_start = (activity.start_time, operator_end_times[earliest_op])
new_end = new_start + activity.duration
assignments[earliest_op].append({
: activity.description,
: activity.start_time,
: new_start,
: new_end
})
operator_end_times[earliest_op] = new_end
new_total_time = (operator_end_times)
original_total_time = (a.end_time a activities)
{
: assignments,
: original_total_time,
: new_total_time,
: original_total_time - new_total_time,
: ( - new_total_time/original_total_time) *
}
def suggest_quick_release_mechanisms(activities):
"""
Suggest engineering improvements for faster changeovers
"""
suggestions = []
for activity in activities:
desc_lower = activity.description.lower()
# Fastener improvements
if any(word in desc_lower for word in ['bolt', 'screw', 'nut', 'fasten']):
suggestions.append({
'activity': activity.description,
'current_method': 'Threaded fasteners',
'improvement': 'Quick-release clamps, cam locks, or quarter-turn fasteners',
'typical_reduction': '70-90%',
'investment_level': 'Medium'
})
# Tool changes
if 'tool' in desc_lower and 'change' in desc_lower:
suggestions.append({
'activity': activity.description,
'current_method': 'Manual tool change',
'improvement': 'Quick-change tool holders with preset tooling',
'typical_reduction': '80-95%',
'investment_level': 'Medium-High'
})
# Positioning/alignment
if (word desc_lower word [, , ]):
suggestions.append({
: activity.description,
: ,
: ,
: ,
:
})
(word desc_lower word [, , ]):
suggestions.append({
: activity.description,
: ,
: ,
: ,
:
})
suggestions
def generate_comparison_report(before_analysis, after_analysis):
"""
Generate before/after SMED comparison report
"""
before_summary = before_analysis.summary()
after_summary = after_analysis.summary()
return {
'changeover': {
'machine': before_analysis.machine_name,
'product_change': f"{before_analysis.from_product} -> {before_analysis.to_product}"
},
'time_comparison': {
'before': {
'total_minutes': before_summary['total_changeover_time'] / 60,
'internal_minutes': before_summary['internal_time'] / 60,
'external_minutes': before_summary['external_time'] / 60
},
'after': {
'total_minutes': after_summary['total_changeover_time'] / 60,
'internal_minutes': after_summary['internal_time'] / 60,
'external_minutes': after_summary['external_time'] / 60
}
},
'improvement': {
'time_reduction_minutes': (before_summary['total_changeover_time'] -
after_summary['total_changeover_time']) / 60,
'percent_reduction': (1 - after_summary['total_changeover_time'] /
before_summary[]) * ,
: ( - after_summary[] /
before_summary[]) *
},
: {
: before_summary[],
: after_summary[],
: before_summary[] - after_summary[]
}
}
def generate_standard_changeover(optimized_analysis):
"""
Create standard work document for changeover
"""
document = {
'title': f"Standard Changeover: {optimized_analysis.machine_name}",
'revision': '1.0',
'date': datetime.datetime.now().isoformat(),
'target_time_minutes': optimized_analysis.summary()['total_changeover_time'] / 60,
'preparation_phase': {
'description': 'Activities to complete BEFORE stopping machine',
'activities': []
},
'changeover_phase': {
'description': 'Activities performed while machine is stopped',
'activities': []
},
'startup_phase': {
'description': 'Activities to complete after starting machine',
'activities': []
}
}
for activity in optimized_analysis.activities:
entry = {
'step': activity.id,
'description': activity.description,
'time_seconds': activity.duration,
'operator': activity.operator,
'tools': activity.tools_required,
'notes': activity.notes
}
if activity.activity_type == ActivityType.EXTERNAL:
if activity.start_time < 0: # Prep phase
document['preparation_phase'][].append(entry)
:
document[][].append(entry)
:
document[][].append(entry)
document
This skill integrates with the following processes:
setup-time-reduction-smed.jskaizen-event-facilitation.jsoee-improvement.js{
"current_state": {
"total_changeover_minutes": 45,
"internal_minutes": 38,
"external_minutes": 7
},
"opportunities": {
"convert_to_external": 5,
"parallel_execution": 3,
"quick_release": 4,
"eliminate": 2
},
"projected_future_state": {
"total_changeover_minutes": 12,
"reduction_percent": 73
},
"implementation_plan": {
"phase_1": "Convert preparation to external",
"phase_2"