smithery/neversight

prompt-design

Design MCP prompts to expose reusable prompt templates. Use when creating parameterized prompts in xmcp.

Installation

$ npx skills add smithery/neversight --skill prompt-design

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More details

Agent compatibility

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Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,798 B
  • docs SUMMARY.md 125 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

Create xmcp Prompt

You are helping the user create a new xmcp prompt. Follow this interactive workflow.

Step 1: Gather Information

Before generating any code, ask the user these questions using AskUserQuestion:

  1. Prompt name (if not provided): What should the prompt be named? (Use kebab-case)
  1. Prompt type: Ask which type of prompt they need:

- Simple - Static prompt text without parameters - Parameterized - Prompt with user-provided parameters (most common) - Multi-content - Returns multiple content blocks (text, images, etc.)

  1. Parameters (if parameterized): What inputs should the prompt accept?

- Parameter name - Type (string, number, enum) - Description - Whether it's optional - Any validation or default values

  1. Role: What role should the prompt assume?

- user - Prompt from user perspective (most common) - assistant - Prompt as assistant response template

  1. Use case: What is the prompt designed for?

- Code review - Documentation generation - Data analysis - Content creation - Other specific task

Step 2: Generate the Prompt

Create the prompt file in src/prompts/:

File Location

src/prompts/{prompt-name}.ts

Prompt Structure Reference

Every xmcp prompt has three main exports:

// 1. Schema (optional) - Define parameters with Zod
export const schema = { /* ... */ };

// 2. Metadata (optional) - Prompt configuration
export const metadata: PromptMetadata = { /* ... */ };

// 3. Handler (required) - Default export function
export default function handler(params?) { /* ... */ }

Quick Reference

Essential Imports

import { type PromptMetadata } from "xmcp";

// For parameterized prompts
import { z } from "zod";
import { type InferSchema, type PromptMetadata } from "xmcp";

Metadata Fields

Field Type Required Description
name string No* Unique prompt identifier
title string No Human-readable title
description string No What this prompt does
role string No "user" or "assistant" (default: user)

*When metadata is omitted, xmcp uses the filename as the prompt name.

Handler Return Types

Return Type Use Case
string Simple text prompt
{ type: "text", text: string } Explicit text content
{ type: "image", data: base64, mimeType: string } Image content
Array<Content> Multiple content blocks

Use Cases for Server-Exposed Prompts

MCP prompts are useful for:

  1. Standardized workflows - Consistent code review, documentation patterns
  2. Complex templates - Multi-step analysis prompts with structure
  3. Domain expertise - Specialized prompts for specific domains
  4. Reusable patterns - Common tasks that benefit from parameterization
  5. Client integration - Prompts that MCP clients can discover and use

Detailed Templates

For complete code templates including:

  • Simple prompt patterns
  • Parameterized prompts with Zod schemas
  • Multi-role conversation prompts
  • Autocompletion support
  • Code review and documentation examples

Read: references/patterns.md


Checklist After Generation

  1. File created in src/prompts/{prompt-name}.ts
  2. If using metadata, ensure it has name, title, and description
  3. Schema uses .describe() for all parameters (if parameterized)
  4. Handler returns appropriate content format
  5. Role is set appropriately for the use case

Suggest running pnpm build to verify the prompt compiles correctly.