aircall_get_predicted_csat

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

Annotations already declare readOnlyHint=true, and the description aligns by using 'Get'. It adds a useful nuance that the score is AI-predicted rather than actual, but does not disclose other behavioral details such as error conditions or response format, which is acceptable given the tool's simplicity.

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 a single, tightly focused sentence with no extraneous information. It front-loads the core action and target, making it immediately understandable.

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 read-only tool with one parameter and no output schema, the description adequately conveys what the tool does and what it returns (the predicted CSAT score). It does not describe return formatting, but the expected return is clear from the description and semantics.

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?

Schema coverage is 100% with call_id fully described as 'The call ID'. The description adds no additional semantic detail about the parameter, but the schema already provides sufficient meaning, so the baseline score of 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 clearly states the verb 'Get' and the specific resource 'AI-predicted customer satisfaction (CSAT) score for a call'. This is concise and unambiguous, and distinguishes it from sibling tools like aircall_get_sentiments or aircall_get_call.

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 implies the tool should be used when an AI-predicted CSAT score for a specific call is needed. However, it does not explicitly contrast it with alternatives or provide context on when not to use it, so guidance is only implied.

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