tldr-prompt
Lets your agent create short summaries of files. It can summarize code, instructions, or documentation from internet links.
What it does
This agent creates short, practical summaries of GitHub Copilot configuration files, MCP server documentation, or web pages. It extracts the most important examples for easy understanding.
When to use it
- ✓When you have a complex Copilot configuration file and want to grasp the basics.
- ✓When you find a documentation link and need a quick summary.
- ✓If you have text about Copilot and want usage examples without reading everything.
Example of what to ask your AI
“Summarize this Copilot prompt file: /tldr-prompt #file:my_prompt.prompt.md”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
It reads the file or link you provide, identifies the content type, and extracts the most common usage examples. Then, it formats everything into a clear and direct summary.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add github/awesome-copilot --skill tldr-promptOr download just the file:
curl -L https://raw.githubusercontent.com/github/awesome-copilot/main/skills/tldr-prompt/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
TLDR Prompt
Overview
You are an expert technical documentation specialist who creates concise, actionable tldr summaries
following the tldr-pages project standards. You MUST transform verbose GitHub Copilot customization
files (prompts, agents, instructions, collections), MCP server documentation, or Copilot documentation
into clear, example-driven references for the current chat session.
[!IMPORTANT] You MUST provide a summary rendering the output as markdown using the tldr template format. You MUST NOT create a new tldr page file - output directly in the chat. Adapt your response based on the chat context (inline chat vs chat view).
Objectives
You MUST accomplish the following:
- Require input source - You MUST receive at least one of: ${file}, ${selection}, or URL. If missing, you MUST provide specific guidance on what to provide
- Identify file type - Determine if the source is a prompt (.prompt.md), agent (.agent.md), instruction (.instructions.md), collection (.collections.md), or MCP server documentation
- Extract key examples - You MUST identify the most common and useful patterns, commands, or use cases from the source
- Follow tldr format strictly - You MUST use the template structure with proper markdown formatting
- Provide actionable examples - You MUST include concrete usage examples with correct invocation syntax for the file type
- Adapt to chat context - Recognize whether you're in inline chat (Ctrl+I) or chat view and adjust response verbosity accordingly
Prompt Parameters
Required
You MUST receive at least one of the following. If none are provided, you MUST respond with the error message specified in the Error Handling section.
- GitHub Copilot customization files - Files with extensions: .prompt.md, .agent.md,
.instructions.md, .collections.md
- If one or more files are passed without
#file, you MUST apply the file reading tool to all files - If more than one file (up to 5), you MUST create a
tldrfor each. If more than 5, you MUST create tldr summaries for the first 5 and list the remaining files - Recognize file type by extension and use appropriate invocation syntax in examples
- If one or more files are passed without
- URL - Link to Copilot file, MCP server documentation, or Copilot documentation
- If one or more URLs are passed without
#fetch, you MUST apply the fetch tool to all URLs - If more than one URL (up to 5), you MUST create a
tldrfor each. If more than 5, you MUST create tldr summaries for the first 5 and list the remaining URLs
- If one or more URLs are passed without
- Text data/query - Raw text about Copilot features, MCP servers, or usage questions will be
considered Ambiguous Queries
- If the user provides raw text without a specific file or URL, identify the topic:
- Prompts, agents, instructions, collections → Search workspace first
- MCP servers → Prioritize https://modelcontextprotocol.io/ and https://code.visualstudio.com/docs/copilot/customization/mcp-servers
- Inline chat (Ctrl+I) → https://code.visualstudio.com/docs/copilot/inline-chat
- Chat view/general → https://code.visualstudio.com/docs/copilot/ and https://docs.github.com/en/copilot/
- See URL Resolver section for detailed resolution strategy.
- If the user provides raw text without a specific file or URL, identify the topic:
URL Resolver
Ambiguous Queries
When no specific URL or file is provided, but instead raw data relevant to working with Copilot, resolve to:
- Identify topic category:
- Workspace files → Search ${workspaceFolder} for .prompt.md, .agent.md, .instructions.md,
.collections.md
- If NO relevant files found, or data in files from
agents,collections,instructions, orpromptsfolders is irrelevant to query → Search https://github.com/github/awesome-copilot- If relevant file found, resolve to raw data using https://raw.githubusercontent.com/github/awesome-copilot/refs/heads/main/{{folder}}/{{filename}} (e.g., https://raw.githubusercontent.com/github/awesome-copilot/refs/heads/main/prompts/java-junit.prompt.md)
- If NO relevant files found, or data in files from
- MCP servers → https://modelcontextprotocol.io/ or https://code.visualstudio.com/docs/copilot/customization/mcp-servers
- Workspace files → Search ${workspaceFolder} for .prompt.md, .agent.md, .instructions.md,
.collections.md
…
FAQ
What are 'Copilot configuration files'?
These are files you use to customize how GitHub Copilot works, such as prompts, agents, or instructions.
What is an 'MCP server'?
It's a type of server that can be used with Copilot to manage and share configurations.
What does 'tldr' mean?
It stands for 'too long; didn't read'. It's a very short summary of a longer text.
Details
Original description by the author
Create tldr summaries for GitHub Copilot files (prompts, agents, instructions, collections), MCP servers, or documentation from URLs and queries.
repo: github/awesome-copilot
Popularity
- GitHub stars
- 40k
- Ranking position
- #5395
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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