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Prompts Menu

prompts_menu
Read-only

Access the InsightfulPipe prompt catalog for any platform.

Use list_platforms to see all supported platforms.

Operations:

  1. request='menu', platform='' – List public prompts

  2. request='menu', platform='', prompt_type='custom', workspace_id= – List custom prompts

  3. request='prompt_details', platform='', prompt_id= – Get public prompt text

  4. request='prompt_details', platform='', prompt_id=, is_custom=True, workspace_id= – Get custom prompt text

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

Input Schema

NameRequiredDescriptionDefault
requestYes
platformYes
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

A3.9/5.0
Behavior3/5

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

The annotations already establish that this is a read-only, non-destructive, closed-world operation. The description adds useful scope details, especially that custom prompt access requires workspace_id and is_custom, but it does not describe permissions, error behavior, or pagination. Given the annotation coverage, a 3 is appropriate.

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, structured as a short purpose statement followed by numbered operation patterns, and contains no filler. Every line helps the agent choose the correct parameter combination.

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?

For a six-parameter polymorphic tool with no schema parameter descriptions, the description successfully documents all four invocation patterns, and the output schema can explain return values. Minor gaps remain around platform enumeration, error behavior, and whether any prompt listing is limited or paginated.

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 description coverage is 0%, so the description must carry the parameter meaning, and it largely does by mapping request, platform, prompt_type, workspace_id, prompt_id, and is_custom to concrete operation patterns. It does not explain accepted platform values beyond referring to list_platforms, nor does it clarify prompt_type values other than 'custom'.

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

Purpose4/5

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

The description clearly states that this tool accesses the InsightfulPipe prompt catalog and then enumerates the four supported operations: listing public/custom prompts and fetching public/custom prompt text. It distinguishes its own request modes well, though it does not directly contrast itself with siblings such as query_data or query_contexts.

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?

The numbered operations provide explicit parameter combinations for each use case, including when to use workspace_id and is_custom for custom prompts. It also points to list_platforms to discover valid platform values, but it does not state exclusions or when another sibling tool would be more appropriate.

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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