design

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

No annotations provided, so description carries full burden. It discloses return values and a technical note about rack-level design standardization. Lacks details on side effects (likely read-only computation), but the description is honest about capabilities.

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?

Two sentences: first states function and returns, second gives usage guidance and a technical nuance. Front-loaded, no redundant information. Every sentence earns its place.

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?

With 6 parameters, no output schema, and a nested object, the description provides adequate overview but could elaborate on when cost/timeline are available. Technical note on Vera Rubin is helpful but not comprehensive for all edge cases.

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% with good parameter descriptions. The main description adds minimal value beyond highlighting key parameters (IT load, rack density, GPU generation, site area, region) and optional overrides. Baseline 3 is appropriate.

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 sizes an AI data center and lists specific return values (rack count, design PUE, total MVA, cost estimate, timeline). It distinguishes from sibling tools by focusing on sizing/estimation rather than layout or validation.

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?

Explicitly says 'Use this when the user asks to dimension, plan, or estimate an AI data center' with specific GPU generations. Does not explicitly mention alternatives or when not to use, but the context is clear enough for an agent to select appropriately.

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