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YouTube MCP by InsightfulPipe

YouTube Prompts

prompts_menu
Read-only

Access YouTube prompt catalog with 4 operations:

  1. List Public Prompts: • request='menu' - No additional params needed • Returns: All public/system prompts available for YouTube

  2. List Custom Prompts: • request='menu', prompt_type='custom', workspace_id= • Returns: All custom prompts for the specified workspace

  3. Get Public Prompt Details: • request='prompt_details', prompt_id= • Returns: Full text/details of a public prompt

  4. Get Custom Prompt Details: • request='prompt_details', prompt_id=, is_custom=True, workspace_id= • Returns: Full text/details of a custom prompt

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": {
      "request": "<request>"
    },
    "name": "prompts_menu"
  }
}

Input Schema

NameRequiredDescriptionDefault
requestYes
is_customNo
prompt_idNo
prompt_typeNo
workspace_idNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds useful behavior — which operations return lists vs full prompt text and that custom operations require workspace_id — but does not discuss auth needs, rate limits, or error conditions.

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 front-loaded with the catalog scope and uses a compact numbered structure that matches the four operational modes. Each bullet earns its place by pairing an invocation pattern with the expected return.

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

Completeness4/5

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

With an output schema present, the description need not detail return structures, and it provides enough routing information for all four operations. However, the relationship between prompt_type='custom' and is_custom=True is not clarified, and no workspace prerequisite context is given beyond the parameter listing.

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

Parameters4/5

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

Schema coverage is 0%, so the description must carry parameter meaning; it does so well by mapping request values, prompt_type, workspace_id, prompt_id, and is_custom to concrete operations. It does not explain nullable/default behavior or the semantic difference between prompt_type='custom' and is_custom=True, which could cause confusion.

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 states a specific resource — the YouTube prompt catalog — and enumerates four concrete operations (list public/custom, get public/custom details). This clearly distinguishes it from generic siblings like execute_action, query_contexts, and query_data.

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

Usage Guidelines4/5

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

It gives explicit parameter combinations for each of the four operations, so an agent can route between public vs custom listing and detail retrieval. It does not mention when to choose this tool over sibling tools or when not to use it, which leaves a small gap.

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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