annotate_models

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

With no annotations provided, the description carries full burden. It discloses that the tool overwrites any existing note and that notes appear in search results and favourites, but does not mention authentication, rate limits, error behavior, or whether notes are private to the user.

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 concise with three short paragraphs. The first sentence front-loads the purpose, and the args list is structured. Every sentence provides value without redundancy.

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 annotation tool with 2 parameters and an output schema, the description is nearly complete. It explains the operation, side effects (overwrite), and where notes appear. It could mention whether the model must exist or if errors occur for invalid models, but overall it's thorough.

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%, so the description must compensate. It fully describes both parameters: 'model' with format and example ('e.g. openai/gpt-5.2'), and 'note' with purpose and overwrite behavior. This adds significant meaning beyond the schema.

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 tool's purpose: 'Add or update a personal note on a model.' It uses specific verbs and resource, and distinguishes itself from sibling tools by explaining that notes appear in search_models results and favourites list, which clarifies its unique role.

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 when to use (when wanting to annotate a model) but lacks explicit 'when not to use' or alternatives. It provides context on where notes appear, but no guidance on conditions like model existence or permission requirements.

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