Get feedback stats

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

With no annotations, the description carries the full burden, and it does disclose the shape of what comes back (total plus breakdowns by type and classification status), which implies a read-only aggregate. It says nothing about scope (all feedback vs. filtered), freshness, permissions, or the format of the breakdown, leaving real gaps for a tool with zero annotation coverage.

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 sentence that front-loads the primary fact (it returns a total) and then the secondary breakdown dimensions. No filler, no restatement of the title beyond what is necessary.

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?

There is no output schema, so the description must convey the return shape, and it does so at a high level: total count, breakdown by type, breakdown by classification status. It stops short of describing field names or whether the breakdown values are counts vs. percentages, which is the only meaningful remaining gap for a zero-parameter stats tool.

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 takes no parameters, so the baseline is 4 and there is nothing for the description to compensate for. The one sentence that could matter — whether the stats are global or scoped — is not addressed, but with an empty schema there is no parameter ambiguity to resolve.

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 and resource ('Returns the total number of feedback entries in Feedback Hub') and enumerates the breakdown dimensions, so the aggregate nature of the tool is unmistakable. It does not explicitly contrast with the sibling list_feedback, but the count/breakdown framing distinguishes it implicitly.

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?

Usage is only implied: an agent can infer this is for summary counts rather than enumerating individual entries, but the description never says when to prefer it over list_feedback or whether the two cover the same data set. No exclusions or prerequisites are stated.

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