list_models

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

No annotations exist, so the description carries the burden. It does disclose the important behavioral trait that results are live from the customer's Odoo when a connector is configured and otherwise bundled samples, which explains why the result set varies. It says nothing about pagination, result size, or how `search` filters.

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 compact sentences, front-loaded with the resource and immediately followed by the workflow hand-off. No filler, and the parenthetical source caveat is placed where it reads naturally.

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 tool with no output schema and no annotations, the description covers purpose, source-of-data variability, and downstream usage. The gap is the undocumented `search` parameter, which is the only structured field an agent must reason about.

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 single `search` parameter is never mentioned in the description, so nothing indicates whether it matches model name, technical name, or description, or whether it is a substring or prefix match. The only semantic hint ('model' value) concerns the output, not the input.

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?

States a specific verb and resource ('List the Odoo models a template can bind to') and disambiguates from the many list_* siblings by naming the domain concept ('models', not templates/starters/parts). An agent immediately knows this returns Odoo model names, not records.

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?

Gives downstream usage explicitly: 'Use the `model` value as layout.bind_model', which tells the agent where this fits in the workflow. It stops short of naming alternatives (e.g. get_fields for per-model fields) or stating when not to call it.

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