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 of behavioral disclosure. It mentions the tool 'Returns a formatted list of matching models,' which gives some output context, but it doesn't cover critical aspects like rate limits, authentication needs, error handling, or pagination behavior. For a search tool with no annotation coverage, this leaves significant gaps in understanding its operational traits.

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 well-structured. It starts with a clear purpose statement, followed by a bulleted list of parameters with concise explanations, and ends with a note on return values. Every sentence earns its place without redundancy, making it easy to scan and understand quickly.

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 the complexity (a search tool with 4 parameters), no annotations, and no output schema, the description is moderately complete. It covers the purpose and parameters adequately but lacks behavioral details like error handling or rate limits. The absence of an output schema means the description's mention of 'formatted list' is helpful but not fully compensatory, leaving room for improvement 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?

The schema description coverage is 0%, so the description must compensate for the lack of parameter documentation in the schema. It successfully adds meaning by listing all four parameters with brief explanations, including defaults for 'count' and 'downloadable.' This provides clear semantics beyond the schema's basic titles, though it could be more detailed (e.g., explaining category formats or query syntax).

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.' It specifies the verb ('search') and resource ('models on Sketchfab'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'search_polyhaven_assets' beyond the platform name, which is why it doesn't reach a score of 5.

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 different platforms or 'get_sketchfab_status' for status checks, nor does it specify prerequisites or exclusions. Usage is implied only by the tool name and description, lacking explicit context.

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