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Pretty Prompt MCP Server

Pretty Prompt MCP Server

by charliemday
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

save_to_library

Save prompts to your Pretty Prompt library to keep them organized and reusable across AI editors.

Instructions

Save a prompt to the user's Pretty Prompt library.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "prompt": "<prompt>"
    },
    "name": "save_to_library"
  }
}

Input Schema

NameRequiredDescriptionDefault
titleNoOptional display title
promptYesThe prompt text to save

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.5/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure. It only states the action (save) and destination (library), but does not mention side effects (e.g., overwrites or duplicates), authentication requirements, return values, or error behavior. This is a significant gap for a write operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence with no redundant information. It is front-loaded with the action and resource, making it easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple, and the schema fully documents parameters, but the description lacks context about what happens after saving (e.g., return value or confirmation) and does not reference sibling tools for follow-up actions (e.g., viewing via list_library_prompts). This leaves some gaps for practical use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already describes both parameters (title and prompt) with 100% coverage. The description does not add any additional meaning or context to the parameters, so the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Save a prompt to the user's Pretty Prompt library' uses a clear verb (save) and resource (prompt to library), and distinguishes this tool from siblings like list_library_prompts (listing) and move_prompt_to_folder (moving). It is specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to use this tool versus alternatives, such as 'use for creating new prompts, not for moving existing ones.' However, the verb 'save' implies it is for adding new prompts, and the sibling names provide some context. This is implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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