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conversation-analyzer

Analyze Claude Code conversation history to identify usage patterns and workflow improvements.

4|1|Updated Jan 13, 2026
Search Tags:#productivity#code history#conversation analysis#workflow optimization#usage patterns#automation opportunities
One-click install
npx skills add https://github.com/rm2thaddeus/Aitor_Skills --skill conversation-analyzer-rm2thaddeus
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: conversation-analyzer
Source: https://github.com/rm2thaddeus/Aitor_Skills/tree/main/conversation-analyzer
Command: npx skills add https://github.com/rm2thaddeus/Aitor_Skills --skill conversation-analyzer-rm2thaddeus

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires json, re, collections, datetime, pathlib, and includes scripts (resource) components.

What problem does it solve?

This Skill helps users understand their interaction patterns with Claude Code, identify inefficiencies, and discover opportunities for workflow improvement by analyzing conversation history.

Core Features & Use Cases

  • Usage Pattern Analysis: Identifies request types, active projects, and time-of-day usage.
  • Mistake Identification: Detects common errors, vague requests, and repetitive tasks.
  • Automation Opportunities: Suggests ways to automate recurring commands or workflows.
  • Use Case: A user wants to know how they can be more efficient with Claude Code. They run this skill, which analyzes their past interactions and provides a report highlighting that they frequently ask for similar code fixes, suggesting they create a reusable script or skill for those tasks.

Quick Start

Use the conversation-analyzer skill to analyze your Claude Code history.

Frequently Asked Questions about conversation-analyzer

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

FAQPage Schema
How do I analyze Claude Code conversation history to identify usage patterns?▼

You can analyze Claude Code conversation history by processing the local `~/.claude/history.jsonl` file to identify request types, track project activity, and categorize time-based usage patterns. The analysis generates detailed reports highlighting your workflow trends.

How do I find repetitive tasks in my Claude Code history for automation opportunities?▼

To find repetitive tasks for automation, the conversation analyzer scans your local history file to detect recurring commands and similar code fixes. It then suggests creating reusable scripts or skills to automate those recurring workflows.

Can I track common mistakes and errors in my Claude Code interactions?▼

Yes, you can track common mistakes by analyzing your conversation history for error keywords and vague requests. The skill categorizes these errors to help you identify inefficiencies and improve your request clarity.

Does the conversation analyzer require any specific dependencies to process history files?▼

The conversation analyzer relies on standard Python dependencies including `json`, `re`, `collections`, `datetime`, and `pathlib` to process the `~/.claude/history.jsonl` file. These libraries handle data parsing, pattern matching, and time-based activity analysis.

What is the best way to optimize my workflow when using Claude Code?▼

The best way to optimize your workflow is to analyze time-based usage patterns and identify repetitive commands in your conversation history. The generated report provides actionable recommendations to streamline your interactions and automate recurring tasks.

Why does my Claude Code usage analysis require a local JSONL file?▼

The usage analysis requires the local `~/.claude/history.jsonl` file because it contains the raw conversation logs needed to categorize request types and track project activity. The Python script processes this structured data to generate actionable workflow reports.

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