conversation-compiler

Convert Claude JSONL logs into .txt, .min.txt, and .view.txt outputs.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/kylesnowschwartz/dotfiles --skill conversation-compiler
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: conversation-compiler
Source: https://github.com/kylesnowschwartz/dotfiles/tree/main/claude/skills/conversation-compiler
Command: npx skills add https://github.com/kylesnowschwartz/dotfiles --skill conversation-compiler

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Claude conversation logs are often large and hard to read, search, and recall in context. The skill transforms raw JSONL transcripts into readable, structured views that preserve conversation context for efficient analysis and recall.

Core Features & Use Cases

  • Compile Claude Code JSONL logs into adaptive views for reading, searching, and context recovery.
  • Output three formats per conversation: a full transcript (.txt), a concise overview (.min.txt), and a search-focused view (.view.txt).
  • Support multi-file processing and automatic extraction of embedded media/documents for reference.

Quick Start

Run VCC.py on a Claude JSONL file to produce a full transcript, a concise overview, and an optional searchable view alongside the input.

Frequently Asked Questions about conversation-compiler

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I convert Claude JSONL conversation logs into readable text?

To convert Claude JSONL conversation logs into readable text, run the VCC.py script on your JSONL file. It processes the raw transcript data to generate structured .txt outputs, preserving conversation context for efficient reading and context recall.

What is the best way to search through large Claude conversation transcripts?

The best way to search large Claude conversation transcripts is by generating a search-focused .view.txt output. Compiling the JSONL logs into this adaptive view allows efficient context recovery and targeted searching across single or multiple conversation files.

Can I process multiple JSONL files at once to extract conversation overviews?

Yes, you can process multiple JSONL files at once. The skill supports multi-file processing to automatically generate per-conversation transcripts, concise .min.txt overviews, and tool-call summaries while extracting embedded media references.

How does compiling JSONL logs into adaptive views help with context recall?

Compiling JSONL logs into adaptive views helps context recall by transforming large, hard-to-read raw JSONL data into structured .txt, .min.txt, and .view.txt formats. These outputs preserve conversation context for efficient analysis and quick information retrieval.

Do I need any external dependencies to extract media from Claude JSONL logs?

No external dependencies are required to extract media from Claude JSONL logs. The skill operates standalone using its internal scripts to automatically extract embedded media and document references during the multi-file JSONL processing workflow.