BlenderMCP

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 mentions the tool 'Returns a formatted list of matching models,' which gives basic output information, but lacks critical behavioral details such as rate limits, authentication requirements, pagination behavior, error handling, or what 'formatted list' entails. For a search tool with no annotation coverage, this is insufficient.

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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by a bulleted list of parameters with concise explanations. Every sentence earns its place with no redundant information, making it easy to scan and understand.

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?

Given no annotations and no output schema, the description partially compensates by explaining parameters and stating the return type. However, it lacks details on output format, error cases, and behavioral constraints. For a search tool with 4 parameters and no structured output documentation, this is minimally adequate but leaves gaps in operational context.

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 adds meaningful semantics for all 4 parameters: 'query' as 'Text to search for,' 'categories' as 'Optional comma-separated list of categories,' 'count' as 'Maximum number of results to return (default 20),' and 'downloadable' as 'Whether to include only downloadable models (default True).' This provides clear usage context beyond the bare 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 clearly states the tool's purpose: 'Search for models on Sketchfab with optional filtering.' This specifies the verb ('search'), resource ('models on Sketchfab'), and scope ('optional filtering'). However, it doesn't explicitly differentiate from sibling tools like 'search_polyhaven_assets' beyond the platform name.

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 no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'search_polyhaven_assets' for cross-platform comparisons, nor does it specify prerequisites or scenarios where this search is preferred over direct downloads or other model-related operations.

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