customerthermometer_get_comments

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

With no annotations, the description must disclose behavior on its own. It identifies the operation as a read and lists optional filters, but it does not describe pagination/limit semantics, response shape, or whether filters combine. This leaves the agent without important behavioral context beyond the operation itself.

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?

A single front-loaded sentence states the action and resource first, then the optional filters. There is no filler or redundant repetition of schema details.

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 read-only tool with five optional parameters and no output schema or annotations, the description is minimal but covers the core purpose and filter dimensions. It doesn't explain default behavior, response format, or filter interactions, which are meaningful gaps given the absence of annotations and output schema.

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?

All five parameters are already described in the schema (100% coverage), so the description adds no new parameter-level detail. It does summarize the filter dimensions (temperature, blast, date range), which matches parameters but doesn't exceed the schema. Baseline 3 applies.

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 specific verb ('Get') and resource ('free-text comments left with survey responses'), and the optional filter clause adds scope. This clearly separates it from sibling tools like get_nps_value and get_happiness_value, which target metrics rather than comments.

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 tells the agent the operation and filter options, so usage is implied, but it does not explicitly say when to choose this tool over get_blast_results or get_nps_value, nor does it mention exclusions. There are no alternative tool references, leaving selection guidance mostly to inference.

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