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Ads Prompts

prompts_menu
Read-only

Browse the ads prompt catalog.

  1. request='menu' – List public/system prompts (optionally pass workspace_id + prompt_type).

  2. request='prompt_details' – Fetch prompt body by prompt_id. Set is_custom=True + workspace_id for workspace prompts.

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

A4.1/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=true, so the description carries the rest: it discloses that one mode returns a listing while the other returns a full prompt body, and it surfaces the non-obvious coupling that workspace prompts need both is_custom=True and workspace_id. It doesn't cover pagination, listing size, or error behavior when prompt_id is wrong, so it's not a 5.

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?

Front-loaded one-line purpose followed by a two-item mode list; every clause carries information an agent needs to pick a request value. No filler or restatement of the title.

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, return formatting needn't be described, and the read-only safety profile is covered by annotations. The remaining gaps — valid prompt_type values and the implicit prompt_id requirement per mode — are minor but real for a 5-parameter tool.

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 compensate and largely does — it explains the meaning of request's two enum values, prompt_id, workspace_id, prompt_type, and is_custom. The gap is prompt_type: no allowed values or examples are given for a free-form string, and it isn't stated that prompt_id is effectively required for the prompt_details mode.

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 opens with a specific verb+resource ('Browse the ads prompt catalog') and enumerates the two operations the tool supports. An agent can tell exactly what domain this touches; the only shortfall is that it doesn't differentiate from the listed siblings (execute_action, query_contexts, query_data), though those are unrelated rather than competing tools.

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 list gives clear conditional guidance: request='menu' for listing, request='prompt_details' for fetching a body, with the extra condition that workspace prompts require is_custom=True + workspace_id. There are no explicit exclusions or tie-breakers, but the mode-selection context is genuinely usable.

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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