Analyze Field Labs coaching transcription data, calculate session metrics, and generate daily summaries. Use for processing Fieldy voice transcriptions and creating coaching reports.
Instrucciones de origen · Vista previa de solo lectura
name
fieldy-analysis
description
Analyze Field Labs coaching transcription data, calculate session metrics, and generate daily summaries. Use for processing Fieldy voice transcriptions and creating coaching reports.
Fieldy Analysis
Process and analyze Field Labs coaching transcription data to generate daily email summaries.
{"date":"2026-01-04","transcriptions":[{"timestamp":"2026-01-04T10:30:00.000000+00:00","transcription":"Full text of the transcription...","transcriptions":[{"text":"Individual sentence or phrase"
,
"speaker"
:
"Unknown"
,
"start"
:
0.704
,
"end"
:
7.184
,
"duration"
:
null
}
]
,
"metadata"
:
{
"ip_address"
:
"192.168.1.1"
,
"user_agent"
:
"python-httpx/0.28.1"
,
"received_at"
:
"2026-01-04T10:30:00.000000"
}
}
]
}
Metrics to Calculate
Session Metrics
Total Sessions
Count of transcription entries for the day
Each entry = one coaching session/call
Total Duration
Calculate from start/end times of transcription segments
Sum of all segment durations
Average Session Length
Total duration / number of sessions
Measured in minutes
Session Timeline
Timestamps of each session
Distribution throughout the day
Content Metrics
Total Words
Word count across all transcriptions
Indicates session depth/engagement
Average Words per Session
Total words / number of sessions
Speakers
Identify unique speakers (if available)
Track multi-speaker sessions
Topics/Keywords
Extract common topics from transcriptions
Identify coaching themes
Analysis Scripts
analyze_fieldy.py
Analyze Fieldy transcription data and calculate metrics.
Fall back to word count estimation (150 words/min)
Handle missing duration gracefully
Timezone Handling
Fieldy timestamps are in UTC
Convert to PT for email display
Ensure date boundaries are correct
Error Handling
Handle missing files gracefully
Continue processing if one session fails
Log errors for debugging
Performance
Cache parsed data to avoid re-parsing
Process sessions in parallel if many
Limit keyword extraction to top N
Example Daily Report
Fieldy Daily Summary
Friday, January 4, 2026
Summary:
✓ 12 total coaching sessions
✓ 145 minutes total duration
✓ 12.1 minutes average session length
Timeline:
• First session: 8:15 AM PT
• Last session: 5:45 PM PT
• Most active period: 2:00 PM - 4:00 PM
Top Keywords:
• technique (45 mentions)
• training (38 mentions)
• form (32 mentions)
• practice (28 mentions)
Reference
Fieldy data location: data/fieldy/fieldy_YYYY-MM-DD.json
