List Deepy models

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

With no annotations, the description carries the full burden and does well: it discloses that only opened/available models are returned, grouping by generation type, the `[refs]` marker for reference-file support, and that one call suffices (no truncation/pagination). It does not cover auth, rate limits, or error conditions, so it is not perfect, but it exceeds minimum viability.

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 four sentences, front-loaded with the core action, and every sentence earns its place: it adds availability scope, grouping, refs notation, and usage guidance without redundancy. The use of backticks for `[refs]` is clear and compact.

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 listing tool with no required parameters, no output schema, and no annotations, the description is complete enough: it tells the agent what is returned, the grouping behavior, the refs marker, and that one call is sufficient. It does not describe the exact response format, but that is not essential given the tool's simplicity and the high schema coverage.

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 schema already covers all three parameters with 100% description coverage, so the baseline is 3. The description adds value by explaining the purpose of the filters ('pass type/family/group only to narrow the catalogue') and explicitly says they are not for compensating truncation, which enriches the semantics 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 opens with 'List the AI models available to your Deepy API key', a specific verb and resource, and adds scope details: 'only opened/available models are returned'. It also differentiates from sibling tools by noting grouping and refs markers, making its purpose distinct.

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?

Explicitly instructs 'Use this before estimating or creating a generation', providing clear when-to-use context. It also warns 'never to work around a truncated result', which is a when-not. However, it does not explicitly name alternative sibling tools like deepy_estimate_generation or deepy_get_model, so it stops short of a 5.

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