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prompt-review

Generates MD reports analyzing user prompts and performance across multiple AI chat platforms.

Updated Mar 15, 2026
Search Tags:#report-generation#ai-analysis#tool-usage#prompt-review#logs-analysis#prompts-patterns
One-click install
npx skills add https://github.com/yAtomtom/dotfiles --skill prompt-review-yatomtom
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-review
Source: https://github.com/yAtomtom/dotfiles/tree/main/.claude/skills/prompt-review
Command: npx skills add https://github.com/yAtomtom/dotfiles --skill prompt-review-yatomtom

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

AIエージェント対話履歴を分析し、技術理解度・プロンプティングパターン・AI依存度を推定してレポートを生成する。

Core Features & Use Cases

  • データ収集スクリプトを実行して、クラウドやローカルの複数ツールの対話履歴を統合的に分析する
  • レポートは日本語で reports/prompt-review-YYYY-MM-DD.md に出力され、プロジェクト別サマリーや技術理解度マップを提供する
  • 引数処理ルールや前処理の基準を元に短文肯定応答の除外などの分析前処理を適用する

Quick Start

データ収集スクリプトを実行してデータを取り込み、レポートを reports/prompt-review-YYYY-MM-DD.md に出力してください。

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 identify prompting patterns?▼

To analyze AI chat history, this Skill aggregates dialogue histories from multiple agents to estimate technical understanding and identify prompting patterns. It generates a structured report highlighting strengths, gaps, and growth opportunities with tool usage context.

Can I analyze conversation logs from Claude Code, Cursor, and Copilot Chat together?▼

Yes, conversation logs from Claude Code, Cursor, Copilot Chat, Cline, Roo Code, Windsurf, Antigravity, Gemini CLI, OpenAI Codex, and OpenCode can be analyzed together. The Skill integrates histories across these tools to produce a unified analysis.

What is the best way to generate a prompt review report for multiple AI agents?▼

The best way to generate a prompt review report is running the data collection scripts to aggregate dialogue histories. The output is produced as a structured markdown file in Japanese at reports/prompt-review-YYYY-MM-DD.md.

Does the analysis filter out short affirmative responses before processing?▼

Yes, the analysis applies preprocessing rules that exclude short affirmative responses before evaluating the logs. This ensures the prompting patterns and technical understanding estimates are based on meaningful interactions.

What limitations exist when analyzing AI agent dialogue histories?▼

A limitation is that AI agent dialogue histories require specific data collection scripts to aggregate the logs before analysis. Additionally, the final structured report is output exclusively in Japanese, which may affect readability for non-Japanese users.

When do I need to review AI prompting patterns and technical understanding?▼

You need to review AI prompting patterns when you want actionable improvement across development projects. The analysis reveals strengths and gaps in tool usage context and project associations to optimize agent interactions.

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