TLDR Prompt

Overview

tldr

[!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

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

• 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

    tldr

    for 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
• 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

    tldr

    for each. If more than 5, you MUST create tldr summaries for the first 5 and list the remaining URLs
• 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
      • If no relevant files found, check https://github.com/github/awesome-copilot and resolve to 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)
    • 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.

URL Resolver

Ambiguous Queries

1. 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

       , or

       prompts

       folders 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)
   • MCP servers → https://modelcontextprotocol.io/ or https://code.visualstudio.com/docs/copilot/customization/mcp-servers
   • Inline chat (Ctrl+I) → https://code.visualstudio.com/docs/copilot/inline-chat
   • Chat tools/agents → https://code.visualstudio.com/docs/copilot/chat/
   • General Copilot → https://code.visualstudio.com/docs/copilot/ or https://docs.github.com/en/copilot/
2. Search strategy:
   • For workspace files: Use search tools to find matching files in ${workspaceFolder}
   • For GitHub awesome-copilot: Fetch raw content from https://raw.githubusercontent.com/github/awesome-copilot/refs/heads/main/
   • For documentation: Use fetch tool with the most relevant URL from above
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

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

/tldr-prompt

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.

/tldr-prompt "Prompt files relevant to Java"

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.

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

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

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

Documentation Query

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

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

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

# 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

• 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

• ✓ 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