Get Deepy model details

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It proactively states that closed/unknown models return MODEL_NOT_FOUND and that closed models are never revealed. This is meaningful transparency about error behavior and policy. However, it does not mention authentication, rate limits, or other side effects, but for a read-only fetch this is acceptable.

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 sentences, front-loaded with the main purpose, and includes a critical behavioral note. Every sentence adds value with no 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 single-parameter tool with no output schema and no annotations, the description covers the purpose and error behavior adequately. It lists the contents of the returned schema, which is sufficient. It does not describe the exact response format, but that is not required given the absence of an output schema.

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 coverage is 100% and the schema already documents 'modelName' with an example. The description does not add any additional parameter semantics beyond restating the purpose. Baseline 3 is appropriate because 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 states a specific verb ('Fetch') and resource ('full schema for one model'), listing concrete contents (parameters, reference-file limits, generation type, max prompt length). This clearly distinguishes it from siblings like deepy_list_models (which lists models) and deepy_get_generation (which fetches generation results).

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 makes clear when to use it: to fetch schema details for a specific model. It does not explicitly name alternatives or exclusion criteria, but the context implies it is the tool for single-model schema lookup. The sibling list reinforces this by contrasting with list_models, yet no explicit 'use this instead' guidance is given.

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