/asciinema-tools:summarize

AI-powered iterative deep-dive analysis for large .txt recordings. Uses guided sampling and AskUserQuestion to progressively explore the content.

Philosophy

Large recordings (1GB+) cannot be read entirely. This command uses:

Initial guidance - What are you looking for?
Strategic sampling - Head, middle, tail + keyword-targeted sections
Iterative refinement - AskUserQuestion to drill deeper into findings
Progressive synthesis - Build understanding through multiple passes

Arguments

Argument Description

file

Path to .txt file (converted from .cast)

--topic

Initial focus area (e.g., "ML training", "errors")

--depth

Analysis depth: quick , medium , deep

--output

Save findings to markdown file

Workflow

Phase 1: Initial Guidance

AskUserQuestion: question: "What are you trying to understand from this recording?" header: "Focus" options: - label: "General overview" description: "What happened in this session? Key activities and outcomes" - label: "Key findings/decisions" description: "Important discoveries, conclusions, or decisions made" - label: "Errors and debugging" description: "What went wrong? How was it resolved?" - label: "Specific topic" description: "I'll specify what I'm looking for"

Phase 2: File Statistics

/usr/bin/env bash << 'STATS_EOF' FILE="$1"

echo "=== File Statistics ===" SIZE=$(ls -lh "$FILE" | awk '{print $5}') LINES=$(wc -l < "$FILE") echo "Size: $SIZE" echo "Lines: $LINES"

echo "" echo "=== Content Sampling ===" echo "First 20 lines:" head -20 "$FILE"

echo "" echo "Last 20 lines:" tail -20 "$FILE"

echo "" echo "=== Keyword Density ===" echo "Errors/failures:" grep -c -i "error|fail|exception" "$FILE" || echo "0" echo "Success indicators:" grep -c -i "success|complete|done|pass" "$FILE" || echo "0" echo "Key decisions:" grep -c -i "decision|chose|selected|using" "$FILE" || echo "0" STATS_EOF

Phase 3: Strategic Sampling

Based on file size, sample strategically:

For files < 100MB:

Sample head, middle, tail (1000 lines each)

head -1000 "$FILE" > /tmp/sample_head.txt tail -1000 "$FILE" > /tmp/sample_tail.txt TOTAL=$(wc -l < "$FILE") MIDDLE=$((TOTAL / 2)) sed -n "${MIDDLE},$((MIDDLE + 1000))p" "$FILE" > /tmp/sample_middle.txt

For files > 100MB:

Keyword-targeted sampling

grep -B5 -A20 -i "$TOPIC_KEYWORDS" "$FILE" | head -5000 > /tmp/sample_targeted.txt

Phase 4: Initial Analysis

Read the samples and provide initial findings. Then ask:

AskUserQuestion: question: "Based on initial analysis, what would you like to explore deeper?" header: "Drill down" multiSelect: true options: - label: "Specific timeframe" description: "Jump to a particular section (e.g., 'around line 50000')" - label: "Follow keyword trail" description: "Search for specific patterns and expand context" - label: "Error investigation" description: "Deep dive into errors and their resolution" - label: "Success moments" description: "What worked? What were the wins?" - label: "Generate summary" description: "Synthesize findings into a report"

Phase 5: Iterative Deep-Dive

For each selected focus area:

Extract relevant sections using grep with context
Read and analyze the extracted content
Report findings to user
Ask for next action via AskUserQuestion

AskUserQuestion: question: "Found {N} relevant sections. What next?" header: "Continue" options: - label: "Show me the most significant" description: "Display top 3 most relevant excerpts" - label: "Search for related patterns" description: "Expand search to related keywords" - label: "Move on" description: "I have enough on this topic"

Phase 6: Synthesis

AskUserQuestion: question: "Ready to generate summary. What format?" header: "Output" options: - label: "Concise bullet points" description: "Key findings in 10-15 bullets" - label: "Detailed markdown report" description: "Full report with sections and evidence" - label: "Executive summary" description: "1-paragraph high-level summary" - label: "Save to file" description: "Write findings to markdown file"

Keyword Libraries

Trading/ML Domain

Development Domain

Claude Code Domain

Example Usage

Interactive exploration

/asciinema-tools:summarize session.txt

Focused on ML findings

/asciinema-tools:summarize session.txt --topic "ML training results"

Quick overview

/asciinema-tools:summarize session.txt --depth quick

Full analysis with report

/asciinema-tools:summarize session.txt --depth deep --output findings.md

Example Output

Session Summary: alpha-forge-research_20251226

Overview

Duration: 4 days (Dec 26-30, 2025)
Size: 12GB recording → 3.2GB text
Primary Focus: ML robustness research

Key Findings

1. Training-Evaluation Mismatch (CRITICAL)

MSE loss optimizes magnitude, but Sharpe evaluates direction
Result: 80% Sharpe collapse from 2024 to 2025

2. Fishr λ=0.1 Solution (BREAKTHROUGH)

Gradient variance penalty solves V-REx binary threshold
Feb'24 Sharpe: -6.14 → +6.14

3. Model Rankings

Model	Window	Sharpe
TFT	15mo	1.02
BiLSTM	12mo	0.50

Evidence Locations

Line 15234: "Fishr λ=0.1 SOLVES the V-REx binary threshold problem"
Line 48102: Phase 4 results summary table

Next Steps Identified

TFT 15mo + Fishr training
DSR/PBO statistical validation
Agent research synthesis

Troubleshooting

Issue Cause Solution

File too large Recording exceeds memory limit Use --depth quick for sampling only

No keywords found Wrong domain or sparse content Try different --topic focus area

Sampling timeout Very large file Increase terminal timeout or use grep

grep context error Missing GNU grep brew install grep (BSD grep limits)

Output file not saved Permission denied Check write permissions on --output

Related Commands

/asciinema-tools:convert
Convert .cast to .txt first
/asciinema-tools:analyze
Keyword-based analysis (faster, less deep)
/asciinema-tools:finalize
Process orphaned recordings

summarize

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