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by ai.howseen
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Get competitors

get_competitors
Read-only

Compare the brand with its competitors in AI answers: visibility %, share of voice, average position and sentiment, overall and per engine.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_competitors"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNoEnd date YYYY-MM-DD. Default: now.
fromNoStart date YYYY-MM-DD. Default: all time.
brandNoBrand id, name or domain (from list_brands). Optional when the account has a single brand.
engineNoOptional AI engine filter, comma separated: chatgpt, gemini, perplexity, ai_overviews, ai_mode. Default: all engines.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and closedWorld, so the safety profile is covered. The description adds value by disclosing the metric set and the overall/per-engine aggregation dimension, but says nothing about pagination, rate limits, or what happens when competitor data is sparse.

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?

A single sentence with zero filler, front-loaded with the verb and scope, then the metric list. Every clause carries information an agent needs.

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 usefully enumerates the returned metrics and the per-engine breakdown, which is the main thing an agent would otherwise lack. It is close to complete, though the absence of any indication of competitor-list sourcing (e.g. via add_competitor/remove_competitor) leaves a small 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 100%, so all four parameters (from, to, brand, engine) already carry documented semantics and defaults. The description adds no syntax, date-range, or brand-resolution detail beyond the schema, so baseline 3 applies.

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?

Names a clear verb (compare) and resource (competitors) and enumerates the exact metrics returned: visibility %, share of voice, average position, sentiment, overall and per engine. It implicitly separates itself from the sibling get_visibility by framing the output as a comparison against competitors, but it never names or contrasts with that sibling explicitly.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no prerequisites, and no mention of alternatives such as get_visibility (brand-only) or get_top_sources. The comparative framing implies the use case, but the agent is left to infer when this tool is preferable to the other reporting tools.

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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