add_color_attribute

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 operation (add) and the parameter semantics, but it doesn't disclose side effects (e.g., whether an existing color attribute with the same name is replaced or errors), whether the operation is destructive, or what the return value is. For a mutation tool with zero annotation coverage, this is a significant gap.

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 compact and front-loaded with the main purpose, followed by a concise parameter list. Every sentence earns its place, and the format is scannable. It loses one point because the parameter list is somewhat redundant with the schema, but it's still efficient.

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 mutation tool with no annotations and no output schema, the description is incomplete. It doesn't mention what happens on success/failure, whether the color attribute is created empty or with default values, or how it interacts with existing attributes. An agent would need to infer or experiment to know the full behavior. The parameter semantics are covered, but the behavioral context is missing.

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 does explain all four parameters (object_name, name, domain, data_type) with brief semantic notes, including the enum-like values for domain and data_type. However, it doesn't add much beyond what the schema already shows (e.g., defaults are in the schema, and the description just restates the options). It's adequate but not rich.

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 function: adding a color attribute (vertex color layer) to a mesh. It distinguishes itself from the sibling set by naming the specific resource (mesh color attribute) and the operation (add). It doesn't explicitly name a sibling alternative, but the verb+resource combination is specific enough to differentiate it from tools like set_vertex_color or assign_material.

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 implies usage context by specifying the target object and the domain/data_type options, but it doesn't explicitly state when to use this tool versus alternatives like set_vertex_color or enter_vertex_paint. The parameter descriptions give some context, but there's no explicit when/when-not guidance or mention of prerequisites (e.g., the mesh must exist).

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