lv_dp_list_topics

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

No annotations are provided, so the description carries the full burden. It states that the tool returns a list of topics with both Latvian and English names, which is transparent about the output content for a simple read-only listing. No side effects or complex behaviors need disclosure.

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 two short sentences that front-load the core purpose and then give a practical usage hint. Every word earns its place; no redundancy or 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 simple, parameterless listing tool, the description sufficiently explains what it returns and why it's useful. It doesn't specify output formatting or pagination, but with no output schema and given the small likely result set, it is complete enough for correct invocation.

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?

The tool has zero parameters, and the input schema is empty. Per calibration, a baseline of 4 applies. The description correctly mentions topic IDs only as a use case for other tools, not as parameters here, adding no unnecessary parameter details.

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 uses a specific verb ('List') and resource ('all covered data protection topics'), adding detail that topics have Latvian and English names. It clearly distinguishes this from sibling tools that fetch individual guidelines/decisions or search for them.

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 second sentence ('Use topic IDs to filter decisions and guidelines') provides clear context on why the tool is useful and how it connects to other operations. While it doesn't explicitly say 'use this instead of X', it implies a workflow without needing lengthy alternatives.

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