get_share_of_voiceTwo measurements, kept apart. First, your share of mentions in your own tracked answers against the rivals the engines named there. Second, web mention share: how often a web-scale index of ChatGPT answers mentions you against the brands we compare you with, which is not a rival list. Use get_rivals for who the engines name instead of you.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With readOnlyHint annotation already present, the description adds context about the two measurements being kept apart and the source of the web-scale index (ChatGPT answers). It also clarifies that the comparison set is not a rival list, which is a useful behavioral nuance beyond the annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the key idea ('Two measurements, kept apart.'), then explains each measurement and provides a pointer to get_rivals. No wasted words, and the structure is logical and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a no-parameter, read-only tool without an output schema, the description fully explains what the tool measures and when to use it, including the distinction from get_rivals. Nothing essential is missing for an agent to call it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so schema coverage is 100% by default. The description doesn't need to explain parameters, and the baseline for 0-parameter tools is 4. It adds contextual information about the two measurements without needing parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool measures two distinct metrics: share of mentions in tracked answers against named rivals, and web mention share against compared brands. It uses a specific verb and resource, and clearly distinguishes itself from get_rivals by naming that sibling and explaining the difference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides explicit guidance: 'Use get_rivals for who the engines name instead of you.' This tells the agent when to use this tool versus a specific alternative, and clarifies that the second metric's comparison set is not a rival list.
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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