add_modifier

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it adds modifiers to objects, supports a wide range of modifier types, handles parameter formatting (JSON string for modifier_params), and returns a structured result with success status and details. It doesn't mention error conditions, permissions, or side effects, but covers core operational behavior well.

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 with clear sections: purpose statement, modifier type examples, parameter explanations, return format, and usage examples. It's appropriately sized for a tool with 3 parameters and complex functionality. Some redundancy exists (e.g., listing many modifier types), but overall it's efficient and front-loaded with critical 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?

Given the complexity (3 parameters, 0% schema coverage, no annotations, no output schema), the description is quite complete. It explains what the tool does, details all parameters with examples, describes the return structure, and provides multiple usage scenarios. It could improve by mentioning error cases or integration with sibling tools, but it adequately covers the tool's functionality for an AI agent.

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 fully compensate. It provides extensive parameter semantics: object_name is explained as '目标物体的名称（场景中已存在的对象）' (name of target object, existing in scene), modifier_type is detailed with a comprehensive list of examples and formatting rules (e.g., using underscores for spaces), and modifier_params is clearly defined as a JSON string with examples. This adds significant value 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: '为 3ds Max 场景中的指定物体添加修改器(Modifier)' (adds modifiers to specified objects in 3ds Max scenes). It specifies the exact action ('添加' - add) and resource ('修改器' - modifiers), distinguishing it from sibling tools like create_object, delete_object, or set_object_property that handle different operations.

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 by stating it works on '场景中已存在的物体' (existing objects in the scene), suggesting it should be used after object creation. However, it doesn't explicitly state when to use this tool versus alternatives like set_object_property or execute_maxscript for similar effects, nor does it mention prerequisites or exclusions beyond object existence.

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