Get Aircall call sentiments

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, indicating a safe read operation. The description adds one useful behavioral detail: the requirement of an Aircall AI feature, which acts as a feature gate. However, it does not describe potential error conditions, return format, or what happens when sentiment analysis is unavailable, so the added value beyond annotations is modest.

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 consists of two concise sentences. The first sentence immediately communicates the core function, and the second adds a necessary prerequisite. There is no redundancy or filler, and the structure is front-loaded with the most important information.

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 tool with one parameter, the description covers the action and a key prerequisite. However, there is no output schema and the description does not explain what the sentiment analysis returns (e.g., label, score, per-speaker, or overall). This leaves the agent uncertain about the result shape, although the read-only and idempotent hints provide some safety context. The description is adequate but not fully complete.

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 for call_id has full coverage with a description ('Unique Aircall call ID'). The tool description adds no additional parameter meaning beyond what the schema already provides. Since schema coverage is 100%, the baseline of 3 applies without further contribution from the description.

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 action ('Get sentiment analysis') and the specific resource ('one Aircall call'). This distinguishes it from sibling tools like aircall_get_transcription or aircall_get_summary, which target different analysis types. The tool name and description align well with the intended function.

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 mentions a prerequisite ('Requires the applicable Aircall AI feature') but provides no guidance on when to use this tool versus alternatives like aircall_get_summary or aircall_get_action_items. It does not explain when not to use it or which sibling tools serve overlapping purposes, leaving the agent to infer usage from the name alone.

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