aircall_get_sentiments

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

Annotations already declare readOnlyHint=true, so the read-only nature is covered. The description adds valuable behavioral context by specifying the return format: per-participant sentiment values and the possible value set. This goes beyond the annotation's safety profile, providing insight into what the response contains. It does not introduce any contradiction with annotations.

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 two short sentences that immediately convey the action, the target, and the return value. There is no redundancy or filler. It is front-loaded with the verb 'Get' and the resource, making it efficient and easy to scan.

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 simple one-parameter read-only tool with no output schema, the description provides enough information for an agent to invoke it correctly and understand the expected response shape. The annotations cover the safety profile, and the description covers the functional outcome. No additional context is necessary for this tool's complexity.

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 input schema already covers the only parameter, call_id, with a description ('The call ID'), giving 100% schema_description_coverage. The tool description adds no additional parameter-level semantics beyond implying that the call relates to sentiment analysis. Per the baseline rule, with high schema coverage, a score of 3 is appropriate.

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: retrieving sentiment analysis for a call. It specifies the resource (sentiment analysis), the scope (a call), and the return content (per-participant sentiment values with POSITIVE/NEUTRAL/NEGATIVE). This distinguishes it from sibling tools like get_summary or get_topics, which cover different analytical outputs.

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?

While the description does not explicitly name alternatives or exclusions, the purpose is so specific that the usage context is clear: an agent should use this when it needs per-participant sentiment values for a call. The mention of 'per-participant' helps differentiate it from other call analytics siblings, providing sufficient context without the need for explicit when/when-not statements.

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