prompt-summary

Summarize conversation prompts and classify each as investigation, implementation, or refinement.

23|4|Updated Sep 5, 2013
One-click install
npx skills add https://github.com/drn/dots --skill prompt-summary
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: prompt-summary
Source: https://github.com/drn/dots/tree/main/agents/skills/prompt-summary
Command: npx skills add https://github.com/drn/dots --skill prompt-summary

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you understand the flow of a conversation by summarizing the user's prompts and their purpose, making it easier to track progress or share context.

Core Features & Use Cases

  • Prompt History Review: See a clear, numbered list of all user prompts in a conversation.
  • Prompt Classification: Each prompt is categorized by its intent (investigation, implementation, refinement).
  • Concise Summary: A final line summarizes the prompt count by category.
  • Use Case: After a long coding session, use this Skill to quickly see the sequence of requests that led to the final code, helping you recall your thought process or explain it to a colleague.

Quick Start

Summarize the prompts used in this conversation.

Frequently Asked Questions about prompt-summary

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

FAQPage Schema
How do I summarize prompt history from a long conversation?

To summarize prompt history, this Skill reviews the conversation and generates a numbered list of user prompts, annotating each with concise context. It provides a final summary line counting prompts by phase to help you track conversational flow.

What is the best way to classify conversation prompts by intent?

Classifying conversation prompts by intent is handled automatically by categorizing each user request as investigation, implementation, or refinement. This classification helps you understand the purpose and direction of your conversational context at a glance.

Can I review my prompt engineering effectiveness after a coding session?

You can review prompt engineering effectiveness by generating a summary of your session's prompts. It categorizes each request by phase—investigation, implementation, or refinement—allowing you to recall your thought process and evaluate your request sequencing.

How do I track the phases of a conversation history?

Tracking conversation history phases is done by summarizing the prompt sequence into investigation, implementation, and refinement categories. The Skill outputs a final summary line showing the exact count of prompts for each phase to clarify conversational progress.

Does this tool require any external dependencies to analyze conversation history?

Analyzing conversation history requires no external dependencies or components. The Skill runs independently to read your prompt sequence and classify each entry into investigation, implementation, or refinement phases.

When do I need to summarize prompts from a conversation history?

You need to summarize prompts from a conversation history when you want to recall your thought process, track progress, or share context with a colleague after a long session. It clarifies the sequence of requests that led to your final output.