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oma-recap

Summarize AI tool chat logs into themed Markdown reports.

1|Updated Mar 21, 2026
Search Tags:#workflow#summarization#productivity#AI#conversation#report
One-click install
npx skills add https://github.com/first-fluke/mapple --skill oma-recap
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: oma-recap
Source: https://github.com/first-fluke/mapple/tree/main/.agents/skills/oma-recap
Command: npx skills add https://github.com/first-fluke/mapple --skill oma-recap

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps users quickly analyze and synthesize conversation histories across multiple AI tools, enabling efficient review and reporting processes.

Core Features & Use Cases

  • Conversation Summarization: Collects and condenses AI tool chat logs into themed daily or multi-day summaries.
  • Work Content Grouping: Groups prompts by project or theme rather than tool, providing clearer insights into work flow.
  • Use Case: A team member reviews a week's worth of AI interactions to generate a report on project progress, decision points, and tool usage patterns for their manager.

Quick Start

Use the oma-recap skill to generate a daily summary of my AI conversation history from today using the default date setting.

Frequently Asked Questions about oma-recap

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

FAQPage Schema
How do I summarize AI conversation histories from multiple tools for a weekly report?▼

You can summarize AI conversation histories by parsing local chat logs from tools like Claude, Codex, Gemini, Qwen, and Cursor to generate themed Markdown reports on work activity and tool usage for daily or multi-day periods.

Can I group AI chat logs by project instead of by the AI tool I used?▼

Yes, you can group AI chat logs by project or theme rather than by tool. This grouping method condenses prompts across multiple AI tools to provide clearer insights into your specific work flow.

Does this summarization tool work with local chat logs from Cursor and Gemini?▼

Yes, this summarization tool works with local chat logs from Cursor and Gemini, as well as Claude, Codex, and Qwen, parsing them to produce Markdown summaries suitable for review and documentation.

What is the best way to review a week's worth of AI interactions for project progress?▼

The best way to review AI interactions is to generate a multi-day summary that analyzes conversation histories across AI tools, grouping prompts by project to highlight decision points and tool usage patterns.

What format do the conversation summaries get output in for documentation purposes?▼

Conversation summaries are output in Markdown format. This makes them suitable for review and documentation purposes after parsing and synthesizing your local AI tool chat logs.

When should I not use automated conversation summarization for my AI chat logs?▼

You should not use automated conversation summarization if your local chat logs span unsupported AI tools, require real-time streaming analysis, or need formatting outside of Markdown documentation outputs.

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