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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered by structured data. The description contributes nothing further — no mention of pagination behavior, result volume, or what a "model" listing contains.

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 short sentence with no filler and the resource stated immediately. It is efficient, though it is so terse that it sacrifices useful detail rather than being an exemplar of well-structured completeness.

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?

An output schema exists, so return values need not be explained, and the read-only annotations cover safety. What remains missing — when to prefer this over other discovery tools and how large the result set may be — is minor for such a simple tool, leaving it adequate but not rich.

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 100%: 'limit' (max models, default 100, cap 500) and 'filter' (by technical name or label) are fully documented in the schema. The description adds no syntax or formatting detail beyond that, so the baseline 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 names a clear verb ("Descubre") and resource ("modelos disponibles en Odoo"), so an agent understands it enumerates the Odoo models. It does not, however, differentiate itself from adjacent metadata tools such as odoo_fields_get, which also probes model structure.

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?

There is no explicit guidance on when to call this versus siblings like odoo_fields_get or odoo_execute. Usage (e.g. discovering a model before reading its fields) is left entirely to inference, and no exclusions are stated.

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