List Apps

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It discloses caching for 6 hours, the refresh=true override, and the structure of entries (title and uri). This is strong transparency for a simple read-only listing tool, though it does not mention possible errors or edge cases.

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 tightly written in three short sentences, each earning its place: purpose, field semantics, and cache/refresh behavior. It is front-loaded with the core purpose and contains no filler.

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 single-optional-parameter tool, this description is fully sufficient: it explains what is returned, how to use the returned data, and the only parameter's behavior. The output schema is also present, so return-value details need not be repeated.

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 does: it explains what refresh=true does, the 6-hour cache default, and how the fields map to use with launch_app. This gives the agent more than the raw schema does.

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 states a specific verb and resource: listing applications installed on the TV, indexed by title. It also clarifies the data model (title vs. uri), making the tool's purpose unambiguous and easy to distinguish from the sibling tools like launch_app or list_inputs.

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 clearly tells the agent to use the returned 'title' together with launch_app, providing practical integration context. It does not explicitly say when not to use this tool or name alternatives, but the intended place in the workflow is clear enough.

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