PaperclipOrg
Claude Agent Skill · by Github

Tldr Prompt

Turns verbose GitHub Copilot customization files (.prompt.md, .agent.md, .instructions.md, .collections.md) and MCP server docs into concise tldr-pages format s

Install
Terminal · npx
$npx skills add https://github.com/github/awesome-copilot --skill tldr-prompt
Works with Paperclip

How Tldr Prompt fits into a Paperclip company.

Tldr Prompt drops into any Paperclip agent that handles this kind of work. Assign it to a specialist inside a pre-configured PaperclipOrg company and the skill becomes available on every heartbeat — no prompt engineering, no tool wiring.

S
SaaS FactoryPaired

Pre-configured AI company — 18 agents, 18 skills, one-time purchase.

$27$59
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Source file
SKILL.md304 lines
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---name: tldr-promptdescription: '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` summariesfollowing the tldr-pages project standards. You MUST transform verbose GitHub Copilot customizationfiles (prompts, agents, instructions, collections), MCP server documentation, or Copilot documentationinto 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 onthe 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. Ifmissing, you MUST provide specific guidance on what to provide2. **Identify file type** - Determine if the source is a prompt (.prompt.md), agent (.agent.md),instruction (.instructions.md), collection (.collections.md), or MCP server documentation3. **Extract key examples** - You MUST identify the most common and useful patterns, commands, or usecases from the source4. **Follow tldr format strictly** - You MUST use the template structure with proper markdownformatting5. **Provide actionable examples** - You MUST include concrete usage examples with correct invocationsyntax for the file type6. **Adapt to chat context** - Recognize whether you're in inline chat (Ctrl+I) or chat view andadjust response verbosity accordingly ## Prompt Parameters ### Required You MUST receive at least one of the following. If none are provided, you MUST respond with the errormessage 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 `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 beconsidered **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 When no specific URL or file is provided, but instead raw data relevant to working with Copilot,resolve to: 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 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 ```bash# 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** ```bash/tldr-prompt``` **Agent Response when NO Required Data** ```textError: 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** ```bash/tldr-prompt "Prompt files relevant to Java"``` **Agent Response when Relevant Workspace Files Found** ```textI'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** ```textI'll check https://github.com/github/awesome-copilotFound:- 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** ```bash/tldr-prompt #file:typescript-mcp-server-generator.prompt.md``` **Agent** ```textI'll read the file typescript-mcp-server-generator.prompt.md and create a tldr summary.``` #### Documentation Query **User** ```bash/tldr-prompt "How do MCP servers work?" #fetch https://code.visualstudio.com/docs/copilot/customization/mcp-servers``` **Agent** ```textI'll fetch the MCP server documentation from https://code.visualstudio.com/docs/copilot/customization/mcp-serversand 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 errormessage from Error Handling section2. **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 context3. **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 content4. **Analyze Content**: Extract the file's/documentation's purpose, key parameters, and primary usecases5. **Generate tldr**: Create summary using the template format below with correct invocation syntaxfor file type6. **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: ```markdown# 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