get_conversions

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool 'Answers questions like...' which suggests a query/read operation, but doesn't explicitly state whether this is a read-only tool, what permissions are required, rate limits, or what format the data returns. For a 9-parameter tool with no annotations, this is insufficient.

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 appropriately concise with two sentences: one stating the core purpose and one providing usage examples. Both sentences earn their place by adding value, though the structure could be slightly improved by front-loading more behavioral context.

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 9-parameter tool with no annotations and no output schema, the description provides adequate purpose and usage examples but lacks important behavioral context about permissions, rate limits, and return format. The schema covers parameters well, but the description doesn't compensate for the missing annotation and output information.

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 schema description coverage is 100%, so all parameters are well-documented in the schema itself. The description doesn't add any additional parameter semantics beyond what's already in the schema descriptions. The baseline of 3 is appropriate when the schema does the heavy lifting.

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 clearly states the tool's purpose: 'Get conversion/sales data from Sealmetrics' with specific examples of questions it can answer. It identifies the resource (conversion/sales data) and source (Sealmetrics), but doesn't explicitly differentiate from sibling tools like get_funnel_data or get_microconversions.

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?

The description provides usage context through example questions ('How many sales this month?' or 'Show conversions from Google Ads yesterday'), which implies when to use this tool for conversion/sales queries. However, it doesn't explicitly state when NOT to use it or mention alternatives among sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.