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Share of voice

get_share_of_voice
Read-onlyIdempotent

The workspace's own brand's share of ALL brand mentions in AI answers, and which brands hold the rest -- every brand the models named, each marked as a tracked competitor or not.

Use this tool when the user asks who the AI talks about -- phrases like 'share of voice', 'who gets mentioned most', 'which brands does AI recommend in our space', or 'who else shows up'. Do NOT use to rank against the competitors the user tracks (use get_competitor_comparison, which measures the share of answers that mention each tracked brand).

Returns: own share in percent, own rank, and the top brands with their shares.

Example: 'Which brands does AI mention most when people ask about our category?'

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": {
      "workspace_id": "<workspace_id>"
    },
    "name": "get_share_of_voice"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNoHow many days back to look, counted back from end_date (default today). Default 30, max 90. Ignored when start_date is given. Prompts are re-run on a schedule, so a window shorter than a week can be empty.
end_dateNoOptional end of the window, as an ISO date (YYYY-MM-DD). Default today. Cannot be in the future.
start_dateNoOptional explicit start of the window, as an ISO date (YYYY-MM-DD). A full ISO datetime is accepted and its date is used. Overrides days.
workspace_idYesThe workspace's numeric id, as returned by list_workspaces.
competitor_limitNoHow many other brands to list. Default 5, max 20.

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 readOnly, idempotent, non-destructive and closed-world, so safety needs no restating. The description adds real semantics on top: it counts ALL brands rather than only tracked ones, and flags each brand as tracked or not — a distinction that changes how results should be read. It stops short of discussing latency or result-size limits, and the default 30/max 90-day window semantics live only in the schema.

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?

Clearly sectioned into purpose, when-to-use, when-not-to-use, returns, and example, with the core definition front-loaded in sentence one. The closing example question largely restates the usage-phrase list already given, so it is slightly redundant rather than harmful.

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

Completeness5/5

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

Five parameters with one required, no output schema — and the description steps in with an explicit 'Returns:' line covering own share, own rank, and top brands with shares. Combined with the tracked/untracked flagging and the sibling routing, an agent has everything needed to call and interpret it.

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 coverage is 100%, with days, start_date/end_date precedence and competitor_limit bounds all documented in the schema itself. The description adds no parameter-level detail (no mention of competitor_limit controlling list length, or the date-window behavior), so the baseline 3 applies — the schema does all the work here.

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?

Starts with a specific measurement (own brand's share of ALL brand mentions in AI answers) plus the complementary resource (every other brand named and whether it is tracked). It also explicitly contrasts itself with get_competitor_comparison, so an agent can separate the two without reading either schema.

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

Usage Guidelines5/5

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

Gives both sides of the routing decision: a 'use when' list with concrete user phrasings ('share of voice', 'who gets mentioned most', 'who else shows up') and an explicit 'Do NOT use to rank against tracked competitors' that names the correct alternative and how it differs.

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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