Test Voice Report

test-voice-report Skill

STOP! Are you trying to place a REAL Twilio call?

This skill only simulates calls from TEXT files. It does NOT place real Twilio calls.

For real calls, use /twilio-test-call instead.

Want to...	Use this skill
Test report generation with text	test-voice-report (this one)
Place a real Twilio call	twilio-test-call

🎯 Purpose

Test the voice call summary report system end-to-end with sample conversation transcripts.

Use this skill when:

• Testing changes to the voice_call_summary_report Langfuse prompt
• Validating report quality with different conversation patterns
• Debugging report generation issues
• Creating new test conversations

What This Skill Does

This skill provides a single command to:

1. Create a simulated VOICE conversation from a transcript file
2. Generate the Wren-style call report using the Langfuse prompt
3. Send the report to the couple's GROUP conversation
4. Show a preview of the generated report

Before this skill: Required running 2 separate scripts With this skill: One command, complete workflow

Quick Start

Test with existing transcript

docker compose exec api python src/scripts/test_voice_call_report.py \
  --transcript .claude/skills/test-voice-report/transcripts/yard_chores.txt \
  --duration 480

Create and test new transcript

# 1. Create new transcript file in arsenal (source of truth)
vim arsenal/dot-claude/skills/test-voice-report/transcripts/my_conversation.txt

# 2. Sync to .claude
./arsenal/install.sh

# 3. Test it
docker compose exec api python src/scripts/test_voice_call_report.py \
  --transcript .claude/skills/test-voice-report/transcripts/my_conversation.txt \
  --duration 300

Available Transcripts

Current test transcripts:

• transcripts/yard_chores.txt - Pursuer discussing household chores (8 min call)

To add more:

1. Create new .txt file in arsenal/dot-claude/skills/test-voice-report/transcripts/
2. Add raw conversation text (no special formatting needed)
3. Run ./arsenal/install.sh to sync to .claude/
4. Test with the command above

Script Parameters

docker compose exec api python src/scripts/test_voice_call_report.py \
  --transcript PATH           # Required: Path to transcript file
  --duration SECONDS          # Optional: Call duration (default: 300)
  --group-conversation-id ID  # Optional: GROUP conversation ID (default: 10)
  --simple-parsing            # Optional: Use simple alternating instead of smart parsing

Parameters:

• --transcript: Path to transcript text file
• --duration: Call duration in seconds (affects call_duration_minutes in report)
• --group-conversation-id: Which couple's GROUP conversation to use (default: 10 = camily & daniel)
• --simple-parsing: Use simple sentence-by-sentence alternating instead of smart grouping

Transcript Format

Transcripts are very simple - just raw conversation text:

"I don't want to fight, but we need to talk about the yard."
"Is this about the dogs?"
"Yes. There's poop everywhere."
"I picked some up yesterday."

No special formatting needed:

• ❌ No speaker labels
• ❌ No timestamps
• ❌ No metadata
• ✅ Just the conversation text

Parsing modes:

Smart parsing (default):

• Groups related sentences together
• Switches speaker at questions
• Detects response patterns ("Yeah", "Okay", "So")
• More natural conversation flow

Simple parsing (--simple-parsing flag):

• Alternates speaker every sentence
• More predictable but less natural

What The Report Tests

The generated report should demonstrate:

✅ Attachment Pattern Identification

• Pursuer or Withdrawer classification
• Based on conversation patterns

✅ Ask Better / Listen Better Framework

• Role-specific guidance (NOT generic Gottman)
• Pursuers get "Ask Better" practices
• Withdrawers get "Listen Better" practices

✅ Neuroscience Explanations

• Arousal hijacking (>100 bpm = lose IQ points)
• Connection under threat
• Protest behavior framing

✅ Wren's Voice

• Normalizing, warm, research-backed
• "That intensity isn't 'too much'"
• Reframes conflict as attachment system, not personal failure

✅ Specific Examples

• Quotes from the actual call
• Identifies Ask Better / Listen Better moments
• References specific patterns that showed up

✅ Comprehensive Length

• 800-1200 words
• Multiple sections with emoji headers
• Call Quality Score

Example Output

================================================================================
✅ VOICE CALL REPORT TEST COMPLETE
================================================================================

📊 RESULTS:
   Status: success
   Call SID: SIM543D4BC8308D4C119F215B99E3E9F1
   Message ID: 2997

📝 REPORT PREVIEW:
--------------------------------------------------------------------------------
📊 CALL REPORT - 8 Minutes with Your Partner

🔍 WHAT HAPPENED
In this call, camily and their partner discussed frustrations around
household chores...

🧠 YOUR ATTACHMENT PATTERN: PURSUER
You're a Pursuer—when connection feels threatened, you pursue...

💪 MOMENTS YOU USED ASK BETTER
• "I feel alone in the responsibility." This statement expresses
  vulnerability...
--------------------------------------------------------------------------------

✅ Full report sent to GROUP conversation 10
================================================================================

Troubleshooting

"Conversation not found" error:

• The simulated call was created but lookup failed
• Check that the call_sid printed in Step 1 matches Step 2

"No transcripts found" error:

• Transcript didn't create messages properly
• Try --simple-parsing flag for simpler conversations

Report doesn't match Wren philosophy:

• Check Langfuse staging has correct prompt version
• Refresh prompt cache: Use langfuse-prompt-and-trace-debugger skill
• Verify "production" label is set in Langfuse UI

Import error for test script:

• Script location: api/src/scripts/test_voice_call_report.py
• Make sure it exists and has correct imports

Related Skills

• update-langfuse-staging-server-prompt - Update the voice report prompt
• langfuse-prompt-and-trace-debugger - Debug prompt issues
• run-voice-e2e - Full E2E voice pipeline test

Workflow for Prompt Changes

When updating the voice_call_summary_report prompt:

1. Edit prompt in docs/cached_prompts/voice_call_summary_report_production.txt
2. Push to Langfuse staging (use update-langfuse-staging-server-prompt skill)
3. Test with this skill:

   docker compose exec api python src/scripts/test_voice_call_report.py \
     --transcript .claude/skills/test-voice-report/transcripts/yard_chores.txt
   

4. Review report quality
5. Iterate until satisfied
6. Manually add "production" label in Langfuse UI

Quick Reference

# Test with existing transcript
docker compose exec api python src/scripts/test_voice_call_report.py \
  --transcript .claude/skills/test-voice-report/transcripts/yard_chores.txt \
  --duration 480

# Create new transcript (in arsenal - source of truth)
vim arsenal/dot-claude/skills/test-voice-report/transcripts/new_conversation.txt

# Sync to .claude
./arsenal/install.sh

# Test new transcript
docker compose exec api python src/scripts/test_voice_call_report.py \
  --transcript .claude/skills/test-voice-report/transcripts/new_conversation.txt \
  --duration 300