create_surface_3d

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

No annotations provided, so description carries full burden. Discloses interactivity (WebGL, orbit-able) and return format. Lacks details on limitations (e.g., handling of missing data) or performance implications, but adequate for typical chart creation.

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?

Concise and front-loaded with key information. The first sentence captures the essence. Could trim the second sentence slightly, but overall 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?

Covers purpose, usage, and return values (with output schema). Does not address error conditions, input validation (e.g., requirement for complete grid), or performance considerations. Adequate but incomplete for a tool with 8 parameters.

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 coverage is 100% (baseline 3). The description adds value by explaining that long-format rows are pivoted into a z-value grid, clarifying relationship between data and columns beyond schema definitions.

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?

Description clearly states it creates an interactive 3D surface chart from gridded data, using specific verbs and resource. It distinguishes from sibling 3D tools (e.g., create_scatter_3d) by mentioning the pivoting of long-format data into a grid.

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?

Provides explicit ideal use cases (temperature/air-quality across city × month, terrain surfaces, optimization landscapes). Does not explicitly state when not to use, but for a specialized tool these are sufficient.

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