skill_narrator

Convert structured skill outputs into short conversational chat summaries.

7|Updated May 6, 2026
One-click install
npx skills add https://github.com/tya5/reyn --skill skill-narrator
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: skill_narrator
Source: https://github.com/tya5/reyn/tree/main/src/reyn/stdlib/skills/skill_narrator
Command: npx skills add https://github.com/tya5/reyn --skill skill-narrator

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill converts detailed structured outputs from other skills into short, user-friendly chat replies, enhancing conversational clarity.

Core Features & Use Cases

  • Natural-Language Summarization: Takes the final output of skills and rewrites it as a concise, human-readable message.
  • Context-Aware Replies: Produces responses that fit seamlessly into chat dialogues, making interactions more natural.
  • Use Case: After completing a data analysis skill, generate a brief summary to inform the user about the result without overwhelming detail.

Quick Start

Explain the outcome of the last skill in simple language that a user can understand, such as "The report has been generated" or "No relevant data found."

Frequently Asked Questions about skill_narrator

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

FAQPage Schema
How do I convert structured JSON output into conversational chat replies?

To convert structured JSON output into conversational chat replies, this Skill rewrites complex data into short, natural-language summaries. It focuses on minimal processing to generate human-readable messages that fit seamlessly into dialogue interfaces.

What is natural language summarization for structured skill outputs?

Natural language summarization for structured skill outputs is the process of transforming complex data into concise, understandable updates. This mechanism takes detailed results and rewrites them as user-friendly messages suitable for chat interfaces.

How do I generate context-aware responses from complex data analysis results?

You generate context-aware responses from complex data analysis results by applying this Skill to the final output. It produces brief, natural language updates that inform users about outcomes without overwhelming them with detail.

Can I use this summarization Skill for any structured data needing quick interpretation?

Yes, you can use this summarization Skill for any structured data needing quick interpretation. It applies to any skill that produces complex JSON data, requiring minimal processing to focus on natural language generation.

Does this tool require complex configuration to summarize chat responses?

No, this tool does not require complex configuration to summarize chat responses. It requires minimal processing and operates without dependencies, focusing directly on generating concise, human-readable messages from structured outputs.

When should I avoid using automated natural language generation for user experience updates?

You should avoid using automated natural language generation when your users require the full, unmodified detail of the original structured data. This Skill focuses on short, conversational summaries, so it is not suited for delivering comprehensive reports.