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by ai.rempa
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Get the search demand

get_demand
Read-only

Get how much people search for what each prompt asks, to see which prompts matter most: per prompt, the monthly Google searches of equivalent queries in the project's market (a proxy, since AI assistants publish no prompt volumes), the trend over a year, the brand's visibility and best position on it in the latest update, the competitors named, and the opportunity (searches going to answers that do not name the brand). Per topic, the total demand and the share of AI requests about it (Anthropic Economic Index, Claude.ai usage). Read-only.

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": {
      "project": "<project>"
    },
    "name": "get_demand"
  }
}

Input Schema

NameRequiredDescriptionDefault
topicNoA topic name or id from get_project, to keep only its prompts. Default: all topics.
projectYesThe project: its id or its address (for example "acme-france"), as returned by list_projects.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / project / description
      Previous value: -"The project: its id, or its address (for example \"acme-france\"). See list_projects."New value: +"The project: its id or its address (for example \"acme-france\"), as returned by list_projects."
    • changedInput schema / properties / topic / description
      Previous value: -"A topic name or id to keep only its prompts."New value: +"A topic name or id from get_project, to keep only its prompts. Default: all topics."
  2. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, and the description simply restates 'Read-only.' It adds useful context about data provenance (Google search proxy, Anthropic Economic Index) and the caveat that AI assistants publish no prompt volumes, but it does not disclose freshness, caching, or response behavior beyond 'latest update.'

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

Conciseness4/5

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

The description is dense but front-loaded with the main purpose and then systematically lists per-prompt and per-topic outputs. Every clause contributes to explaining the returned data, though the single long sentence is slightly harder to scan than shorter structured phrasing.

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 no output schema, the description carries the burden of explaining return values, and it does so thoroughly by naming the per-prompt and per-topic metrics and their sources. It is largely complete for an agent to understand what will be returned, though it could mention response format or whether results are paginated.

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 100%, so both parameters are fully documented in the schema. The description adds no additional syntax or filtering semantics beyond what the schema provides, so the baseline of 3 is appropriate.

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 returns search demand for each prompt and topic, including specific metrics such as monthly Google searches, trend, visibility, competitors, and opportunity. The purpose is specific and distinguishable from sibling tools like get_overview or get_perception, though no sibling is explicitly named.

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 implies a use case ('to see which prompts matter most') but does not explicitly say when to choose this tool over alternatives. There are no exclusions or comparisons with sibling tools, leaving the agent to infer selection from the data returned.

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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