Voice AI Margin Index
voice_margin_indexStructured AI voice pricing benchmarks.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
voice_margin_indexStructured AI voice pricing benchmarks.
| 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 no annotations at all, the description carries the full burden of disclosing behavior, but it only says the output is a structured pricing benchmark. It does not explain what data is included, whether it is a snapshot or live, what units/currencies are used, or whether the call is read-only, so the tool's actual runtime behavior remains opaque.
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 extremely short and free of redundancy, but it is not structured as a complete tool directive. The word 'Structured' adds little, and the lack of a verb makes the sentence weak even if concise.
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?
The tool itself is simple because it has no parameters, but with no output schema and no behavioral description, an agent still cannot know what result to expect. The description should at least say that it returns benchmark pricing data and perhaps the format or scope, which it does not.
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 there is no parameter meaning that the description needs to clarify. Consistent with the baseline for 0 params, the lack of parameter-specific documentation is not a defect.
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 names a resource ('AI voice pricing benchmarks') but lacks an operational verb such as 'get' or 'returns', so it reads as a data label rather than a tool action. It is not a tautology, but it also doesn't make clear how this tool differs from the sibling tools like economic_opportunities or live_market_scan.
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?
There is no guidance on when to use this tool versus its siblings, and no exclusions or alternatives are mentioned. The description only implies that this is a benchmark resource, which is too weak to help an agent choose among the available 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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