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prompt-review

Analyze AI agent chat histories to estimate technical understanding and generate Japanese reports.

359|17|Updated Mar 12, 2026
Search Tags:#developer productivity#prompt analysis#ai chat history#technical understanding#prompting patterns#ai dependency
One-click install
npx skills add https://github.com/tokoroten/prompt-review --skill prompt-review-tokoroten
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-review
Source: https://github.com/tokoroten/prompt-review/tree/main/.claude/skills/prompt-review
Command: npx skills add https://github.com/tokoroten/prompt-review --skill prompt-review-tokoroten

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python3.10+, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps you understand your AI interaction patterns by analyzing chat histories, revealing your technical understanding, prompting techniques, and AI dependency levels.

Core Features & Use Cases

  • Comprehensive Analysis: Analyzes logs from various AI tools (Claude Code, Copilot Chat, etc.).
  • Insightful Reports: Generates detailed reports on technical understanding, prompting skills, and AI usage style.
  • Use Case: A team lead can use this Skill to analyze their team's AI chat logs to identify areas where developers might need more training on specific technologies or prompting strategies.

Quick Start

Run the prompt review skill to analyze your chat history for the last 30 days.

Frequently Asked Questions about prompt-review

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

FAQPage Schema
How do I analyze AI chat history to understand prompting patterns and technical levels?▼

You can analyze AI chat history by processing conversation logs from various tools to estimate technical understanding, prompting patterns, and AI dependency levels, generating a detailed report for review.

Can I filter AI agent conversation logs by project name and specific timeframes?▼

Yes, you can filter AI agent conversation logs by specific days and project names, allowing you to target the analysis to exact development cycles and generate focused insights.

Does analyzing AI chat history work with logs from Claude Code and Copilot Chat?▼

Yes, analyzing AI chat history works with logs from multiple tools including Claude Code and Copilot Chat, aggregating diverse AI agent conversation histories into a single comprehensive analysis.

What is the best way to detect secret credentials in AI agent conversation histories?▼

The best way to detect secret credentials in AI agent conversation histories is to run an automated analysis script that scans chat logs during the evaluation of prompting patterns and technical understanding.

Do I need Python 3.10 or higher to analyze AI chat logs?▼

Yes, you need Python 3.10 or higher installed in your environment to run the scripts required for analyzing AI chat logs and generating the Japanese insight report.

What does an AI dependency level report show about developer productivity?▼

An AI dependency level report shows how developers interact with AI tools, revealing their prompting techniques, technical understanding gaps, and overall AI usage style to help identify training needs.

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