anki_list_models

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds value by clarifying the scope ('every note type') and providing concrete built-in examples, which helps set expectations about the return values. 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?

The description is exactly three sentences, with the core purpose front-loaded in the first sentence. Every sentence earns its place: the second gives examples, the third provides a next-step pointer. No wasted words.

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 read-only listing tool with an output schema and clear annotations, the description is complete. It not only states what the tool does but also situates it in a workflow by recommending anki_get_model_fields next, giving the agent enough context to chain tools correctly.

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% for the single parameter (response_format), and the schema fully documents its enum values and default. The description adds no parameter-specific details, so the baseline of 3 applies; the schema does the heavy lifting.

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 'List every note type (model) in the collection' with a specific verb and resource scope, and provides examples of typical built-ins. It distinguishes itself from sibling tools like anki_list_decks by explicitly focusing on models/note types rather than decks.

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 gives explicit guidance on when to use this tool: before adding a note, recommending to follow up with anki_get_model_fields to learn field names. It implies the use case (listing available models) without explicit alternatives or exclusions, but the workflow context is clear.

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