model_details

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

No annotations are present, so the description carries full burden. It states that the tool returns comprehensive metadata including description, instructions, license, tags, and file count. It does not disclose if it's read-only or any side effects, but for a data retrieval tool this is adequate.

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 concise with two short paragraphs. The first line gives the summary, and the second adds parameter details and output content. No redundant information.

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 one-parameter tool with no output schema, the description covers purpose, parameter source, and output content. It does not mention return format or error handling, but it is complete enough for an agent to use 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?

The single parameter thing_id is described as 'Numeric thing ID (from search_models results)', which adds essential context beyond the schema type and requirement. It tells the agent where to obtain the value.

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 'Get full details for a Thingiverse model' with a specific verb and resource. It distinguishes from sibling tools like search_models by specifying that it uses a numeric thing_id from search 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 provides a clear usage pattern: use thing_id from search_models results. It does not explicitly contrast with other model-related siblings like model_files or get_cached_model, but the guidance is sufficient for the primary use case.

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