blend-ai

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 states the tool sets visibility and returns a confirmation dict, but doesn't cover critical aspects like permissions needed, whether changes are reversible, side effects on linked objects, or error conditions. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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 well-structured and front-loaded: the first sentence states the purpose, followed by clear sections for Args and Returns. Every sentence earns its place with no redundancy or fluff, making it efficient and easy to parse.

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 tool's moderate complexity (4 parameters, mutation operation) and lack of annotations or output schema, the description is partially complete. It covers parameters well but lacks behavioral details (e.g., error handling, side effects) and doesn't fully explain the return value ('confirmation dict' is vague). It's adequate but has clear gaps for safe and effective use.

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 effectively explains all four parameters: 'name' (collection name), 'visible' (visibility toggle), 'viewport' (apply to viewport), and 'render' (apply to render), including defaults for the latter two. This adds clear meaning beyond the bare schema, though it could benefit from examples or edge cases.

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: 'Set collection visibility in viewport and/or render.' It specifies the verb ('set'), resource ('collection visibility'), and scope ('viewport and/or render'), which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'set_object_visibility' or 'create_collection', leaving room for improvement.

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 prerequisites (e.g., needing an existing collection), exclusions, or compare it to related tools like 'set_object_visibility' or 'create_collection'. Usage is implied only through the tool name and parameter descriptions, lacking explicit context.

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