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Audit score 70

tldr-prompt

github/awesome-copilot

Turns verbose Copilot files, MCP docs, or documentation URLs into quick tldr-style chat summaries.

What is tldr-prompt?

tldr-prompt is a chat prompt that generates concise, tldr-pages-style summaries of GitHub Copilot customization files (prompts, agents, instructions, collections), MCP server docs, or Copilot documentation. Use it when you want a quick, example-driven reference for a specific file/URL or an ambiguous topic, rendered directly in the chat without creating new files.

  • Accepts a file, URL, or raw text query as input and requires at least one to proceed
  • Identifies the source type (prompt, agent, instructions, collections, MCP docs, or general documentation)
  • Extracts key examples, commands, and usage patterns from the source
  • Outputs a tldr-pages-formatted markdown summary directly in the chat (does not create new files)
  • Resolves ambiguous queries by searching the workspace first, then falling back to github/awesome-copilot or relevant official documentation sites
  • Handles up to 5 files or URLs per request, summarizing each individually

How to install tldr-prompt

npx skills add https://github.com/github/awesome-copilot --skill tldr-prompt
Prerequisites
  • A coding agent/chat environment with file reading and URL fetch tools available (e.g., #file and #fetch support)
  • Access to the source content: local workspace files, a reachable URL, or knowledge of github/awesome-copilot for fallback resolution
Claude Code
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How to use tldr-prompt

  1. 1.Invoke the prompt with /tldr-prompt in chat (inline chat or chat view)
  2. 2.Provide input: a specific file using #file:{{name.prompt.md|.agent.md|.instructions.md|.collections.md}}, a URL using #fetch {{url}}, or a raw text topic/query in quotes
  3. 3.If a query is ambiguous (no file/URL given), let it search your workspace first, then fall back to github/awesome-copilot or relevant documentation sites
  4. 4.Review the generated tldr-format markdown summary rendered directly in the chat (no new file is created)
  5. 5.If multiple files/URLs are detected, review the individual tldr summary produced for each (up to 5)

Use cases

Good for
  • Quickly understand what a .prompt.md, .agent.md, .instructions.md, or .collections.md file does before using it
  • Summarize MCP server documentation into actionable usage examples
  • Get a fast reference for VS Code Copilot or GitHub Copilot documentation on a given topic
  • Summarize multiple Copilot customization files or URLs (up to 5) in one pass
  • Find and summarize relevant prompt/agent files from your workspace or the awesome-copilot repo when you only have a topic, not a specific file
Who it's for
  • Developers using GitHub Copilot or VS Code Copilot Chat who want quick references for custom prompt/agent/instruction files
  • Teams maintaining libraries of Copilot customization files (prompts, agents, instructions, collections) who need quick documentation
  • Users evaluating MCP servers and wanting a concise usage summary
  • Anyone exploring github/awesome-copilot looking for relevant prompt files by topic

tldr-prompt FAQ

What inputs does this skill accept?

At least one of: a specific file (.prompt.md, .agent.md, .instructions.md, .collections.md), a URL (Copilot file, MCP server docs, or Copilot documentation), or a raw text query/topic. If none are provided, it returns an error asking you to supply one.

What happens if I provide a vague topic instead of a file or URL?

It treats it as an ambiguous query: it first searches your workspace for relevant Copilot customization files, and if none are found, it searches github/awesome-copilot or relevant documentation sites (modelcontextprotocol.io, VS Code docs, GitHub Copilot docs) and fetches the raw content to summarize.

Does it create a new file with the summary?

No. It outputs the tldr summary directly in the chat session and does not create a new tldr page file.

How many files or URLs can it summarize at once?

Up to 5 files or 5 URLs will each get their own tldr summary; if more than 5 are provided, it summarizes the first 5 and lists the remaining ones.

Full instructions (SKILL.md)

Source of truth, from github/awesome-copilot.


name: tldr-prompt description: 'Create tldr summaries for GitHub Copilot files (prompts, agents, instructions, collections), MCP servers, or documentation from URLs and queries.'

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:

  1. 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
  2. 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
  3. Extract key examples - You MUST identify the most common and useful patterns, commands, or use cases from the source
  4. Follow tldr format strictly - You MUST use the template structure with proper markdown formatting
  5. Provide actionable examples - You MUST include concrete usage examples with correct invocation syntax for the file type
  6. 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.

URL Resolver

Ambiguous Queries

When no specific URL or file is provided, but instead raw data relevant to working with Copilot, resolve to:

  1. Identify topic category:

  2. Search strategy:

  3. Fetch content:

    • Workspace files: Read using file tools
    • GitHub awesome-copilot files: Fetch using raw.githubusercontent.com URLs
    • Documentation URLs: Fetch using fetch tool
  4. Evaluate and respond:

    • Use the fetched content as the reference for completing the request
    • Adapt response verbosity based on chat context

Unambiguous Queries

If the user DOES provide a specific URL or file, skip searching and fetch/read that directly.

Optional

  • Help output - Raw data matching -h, --help, /?, --tldr, --man, etc.

Usage

Syntax

# UNAMBIGUOUS QUERIES
# With specific files (any type)
/tldr-prompt #file:{{name.prompt.md}}
/tldr-prompt #file:{{name.agent.md}}
/tldr-prompt #file:{{name.instructions.md}}
/tldr-prompt #file:{{name.collections.md}}

# With URLs
/tldr-prompt #fetch {{https://example.com/docs}}

# AMBIGUOUS QUERIES
/tldr-prompt "{{topic or question}}"
/tldr-prompt "MCP servers"
/tldr-prompt "inline chat shortcuts"

Error Handling

Missing Required Parameters

User

/tldr-prompt

Agent Response when NO Required Data

Error: Missing required input.

You MUST provide one of the following:
1. A Copilot file: /tldr-prompt #file:{{name.prompt.md | name.agent.md | name.instructions.md | name.collections.md}}
2. A URL: /tldr-prompt #fetch {{https://example.com/docs}}
3. A search query: /tldr-prompt "{{topic}}" (e.g., "MCP servers", "inline chat", "chat tools")

Please retry with one of these inputs.

AMBIGUOUS QUERIES

Workspace Search

[!NOTE] First attempt to resolve using workspace files. If found, generate output. If no relevant files found, resolve using GitHub awesome-copilot as specified in URL Resolver section.

User

/tldr-prompt "Prompt files relevant to Java"

Agent Response when Relevant Workspace Files Found

I'll search ${workspaceFolder} for Copilot customization files (.prompt.md, .agent.md, .instructions.md, .collections.md) relevant to Java.
From the search results, I'll produce a tldr output for each file found.

Agent Response when NO Relevant Workspace Files Found

I'll check https://github.com/github/awesome-copilot
Found:
- https://github.com/github/awesome-copilot/blob/main/prompts/java-docs.prompt.md
- https://github.com/github/awesome-copilot/blob/main/prompts/java-junit.prompt.md

Now let me fetch the raw content:
- https://raw.githubusercontent.com/github/awesome-copilot/refs/heads/main/prompts/java-docs.prompt.md
- https://raw.githubusercontent.com/github/awesome-copilot/refs/heads/main/prompts/java-junit.prompt.md

I'll create a tldr summary for each prompt file.

UNAMBIGUOUS QUERIES

File Query

User

/tldr-prompt #file:typescript-mcp-server-generator.prompt.md

Agent

I'll read the file typescript-mcp-server-generator.prompt.md and create a tldr summary.

Documentation Query

User

/tldr-prompt "How do MCP servers work?" #fetch https://code.visualstudio.com/docs/copilot/customization/mcp-servers

Agent

I'll fetch the MCP server documentation from https://code.visualstudio.com/docs/copilot/customization/mcp-servers
and create a tldr summary of how MCP servers work.

Workflow

You MUST follow these steps in order:

  1. Validate Input: Confirm at least one required parameter is provided. If not, output the error message from Error Handling section
  2. Identify Context:
    • Determine file type (.prompt.md, .agent.md, .instructions.md, .collections.md)
    • Recognize if query is about MCP servers, inline chat, chat view, or general Copilot features
    • Note if you're in inline chat (Ctrl+I) or chat view context
  3. Fetch Content:
    • For files: Read the file(s) using available file tools
    • For URLs: Fetch content using #tool:fetch
    • For queries: Apply URL Resolver strategy to find and fetch relevant content
  4. Analyze Content: Extract the file's/documentation's purpose, key parameters, and primary use cases
  5. Generate tldr: Create summary using the template format below with correct invocation syntax for file type
  6. Format Output:
    • Ensure markdown formatting is correct with proper code blocks and placeholders
    • Use appropriate invocation prefix: / for prompts, @ for agents, context-specific for instructions/collections
    • Adapt verbosity: inline chat = concise, chat view = detailed

Template

Use this template structure when creating tldr pages:

# command

> Short, snappy description.
> One to two sentences summarizing the prompt or prompt documentation.
> More information: <name.prompt.md> | <URL/prompt>.

- View documentation for creating something:

`/file command-subcommand1`

- View documentation for managing something:

`/file command-subcommand2`

Template Guidelines

You MUST follow these formatting rules:

  • Title: You MUST use the exact filename without extension (e.g., typescript-mcp-expert for .agent.md, tldr-page for .prompt.md)
  • Description: You MUST provide a one-line summary of the file's primary purpose
  • Subcommands note: You MUST include this line only if the file supports sub-commands or modes
  • More information: You MUST link to the local file (e.g., <name.prompt.md>, <name.agent.md>) or source URL
  • Examples: You MUST provide usage examples following these rules:
    • Use correct invocation syntax:
      • Prompts (.prompt.md): /prompt-name {{parameters}}
      • Agents (.agent.md): @agent-name {{request}}
      • Instructions (.instructions.md): Context-based (document how they apply)
      • Collections (.collections.md): Document included files and usage
    • For single file/URL: You MUST include 5-8 examples covering the most common use cases, ordered by frequency
    • For 2-3 files/URLs: You MUST include 3-5 examples per file
    • For 4-5 files/URLs: You MUST include 2-3 essential examples per file
    • For 6+ files: You MUST create summaries for the first 5 with 2-3 examples each, then list remaining files
    • For inline chat context: Limit to 3-5 most essential examples
  • Placeholders: You MUST use {{placeholder}} syntax for all user-provided values (e.g., {{filename}}, {{url}}, {{parameter}})

Success Criteria

Your output is complete when:

  • ✓ All required sections are present (title, description, more information, examples)
  • ✓ Markdown formatting is valid with proper code blocks
  • ✓ Examples use correct invocation syntax for file type (/ for prompts, @ for agents)
  • ✓ Examples use {{placeholder}} syntax consistently for user-provided values
  • ✓ Output is rendered directly in chat, not as a file creation
  • ✓ Content accurately reflects the source file's/documentation's purpose and usage
  • ✓ Response verbosity is appropriate for chat context (inline chat vs chat view)
  • ✓ MCP server content includes setup and tool usage examples when applicable