validate

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

No annotations provided, so description carries full burden. It discloses output types and input modes, but does not state whether the tool is read-only, has side effects, or any authorization requirements. For a validation tool, it likely doesn't modify data, but this isn't explicit.

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 two sentences: first states purpose and output, second explains input modes. No wasted words, front-loaded with key 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 no output schema, the description provides a good overview of output types (severity-classified findings and RFI items). It covers the two input pathways and their implications. Sibling tools are 'design' and 'layout', so validation's role is clear. Could be more detailed on output structure, but adequate.

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 100%, so schema already documents parameters well. Description adds value by clarifying the mutual exclusivity of rawInput vs designSummary and noting that rawInput triggers sizing. This is critical context beyond the 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 validates data center designs against engineering rules (electrical, cooling, etc.) and outputs severity-classified findings and RFI items. It distinguishes from sibling tools 'design' and 'layout' by focusing on 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 to provide either designSummary or rawInput, with explanation of what rawInput triggers. Could be improved by indicating when not to use it, but the context of siblings implies validation is separate.

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