Aggregate Odoo statistics

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

Annotations already declare readOnlyHint and idempotentHint; the description adds a meaningful behavioral trait beyond that, namely that it processes ALL matching records server-side with no pagination limit. No contradictions 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?

Two sentences with the key scoping and alternative-use guidance front-loaded; no wasted wording.

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?

The description is fit for selection and safety context given the annotations and output schema, but the complete absence of parameter-level documentation leaves gaps around what measure/group_by accept and how the domain is expressed. Adequate overall, with clear gaps.

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 description coverage is 0% and the description does not explain the semantics of the required parameters (model, group_by, measure) or the domain array. It names the action and mentions grouping conceptually, but an agent still lacks guidance on valid measure strings, domain syntax, or group_by entries.

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 precise operation ('Run an aggregation (read_group) query on an Odoo model') and explicitly separates it from aidoo_query, so an agent can identify it without opening the schema.

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?

It gives direct selection guidance: 'PREFERRED tool for statistics, totals, counts, averages, and any analysis' and says to use it instead of aidoo_query for stats. This is explicit when-to-use guidance with an alternative named.

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