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. It mentions 'making its effect permanent', which implies a mutation or irreversible change, but doesn't disclose critical behaviors like permissions needed, side effects, or what 'permanent' entails (e.g., whether it modifies the object data directly). This is inadequate for a tool that likely alters state.

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 brief and front-loaded with the core purpose in the first sentence, followed by structured sections for Args and Returns. However, the Args section merely repeats parameter names without adding value, slightly reducing efficiency. Overall, it's well-structured but could be more informative.

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, 0% schema coverage, and an output schema (which handles return values), the description is minimally adequate. It states the purpose and parameters but lacks details on behavior, usage context, and parameter semantics. For a mutation tool with siblings, this leaves significant gaps in understanding.

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 lists the parameters ('object_name' and 'modifier_name') but only repeats their names without adding meaning, such as what constitutes valid names or examples. This fails to address the coverage gap, leaving parameters poorly understood.

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 states 'Apply a modifier to an object, making its effect permanent', which provides a verb ('apply') and resource ('modifier to an object') with a specific outcome ('permanent'). However, it doesn't differentiate from sibling tools like 'add_modifier' or 'remove_modifier', leaving the exact distinction unclear. The purpose is somewhat vague about what 'permanent' means in this context.

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?

No guidance is provided on when to use this tool versus alternatives. With siblings like 'add_modifier' and 'remove_modifier' present, the description fails to explain the relationship or appropriate contexts for applying versus adding/removing modifiers. This leaves the agent without usage direction.

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