validate

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

No annotations are provided, so the description carries full burden. It explains the tool runs an agent, returns per-criterion results, and mentions retry. However, it lacks details on side effects, auth requirements, rate limits, or resource usage, which is a gap for a validation tool.

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 moderately sized with a clear paragraph and a bulleted Args list. Every part adds value, though it could be slightly more concise by trimming redundant phrases like '— e.g.' examples.

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 presence of an output schema (though not shown), the description need not repeat return values. It covers the essential context: when to use, what it does, and parameter semantics. It could mention error handling or edge cases for completeness.

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 has 0% coverage, but the description compensates with a detailed Args section explaining each parameter: artifact (examples like text or file path), declared_type (type name or natural language), sandbox, model (with default), timeout. This adds significant meaning 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's purpose: validate an artifact against a declared type, running a type-checker agent and returning VALID/PARTIAL/INVALID results. It includes a specific use case (after a pipeline step) and distinguishes from siblings implicitly 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?

The description explicitly says 'Use this after a pipeline step to verify the output matches expectations' and advises what to do if validation fails. It does not provide direct comparison with sibling tools, but the usage context is clear.

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