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Google Analytics 4 MCP by InsightfulPipe

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GA4 Prompts

prompts_menu
Read-only

Browse the Google Analytics 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

A4/5.0
Behavior4/5

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

readOnlyHint=true already covers the safety profile, so the description's value is in the conditional behavior it discloses: 'menu' returns public/system prompts while 'prompt_details' retrieves a prompt body, and workspace prompts require a specific flag/ID pairing. It does not mention result limits, pagination, or behavior for an invalid prompt_id.

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?

One scope sentence followed by a two-item numbered breakdown — front-loaded, scannable, and every line supplies routing information. No filler.

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?

An output schema exists, so return shapes need no explanation, and the read-only annotation covers safety. With five parameters at 0% schema coverage the description does most of the work, but the prompt_type ambiguity and silence on failure behavior leave a small completeness gap.

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?

Schema description coverage is 0%, so the description must carry the full burden. It accounts for request (both enum values), prompt_id, is_custom, and workspace_id, but prompt_type is only name-dropped ('optionally pass ... prompt_type') with no indication of its accepted values or effect, leaving one of five parameters effectively undefined.

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?

States a specific verb and resource ('Browse the Google Analytics prompt catalog') and immediately enumerates the two supported request modes, so an agent knows exactly what domain it operates on. It does not explicitly contrast itself with the siblings (execute_action, query_contexts, query_data), but the prompt-catalog scope is distinct enough to be unambiguous.

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 two numbered entries give clear conditional routing: use 'menu' to list, use 'prompt_details' to fetch a body. It also states the prerequisite for workspace prompts ('is_custom=True + workspace_id'). It stops short of naming when another sibling tool would be the better choice.

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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