validate_up_to_1000

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

No annotations are provided, so the description carries full burden. It mentions validation but doesn't disclose behavioral traits such as what validation entails (e.g., checks, errors), performance expectations, rate limits, or output format. This leaves significant gaps for a tool with no structured safety hints.

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 a single, clear sentence with zero waste—it directly states the tool's function and input constraint. It's appropriately sized and front-loaded, making it efficient for an agent to parse.

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, no output schema, and a vague purpose, the description is incomplete. It doesn't explain what validation means, what happens with invalid inputs, or the return values, leaving the agent with insufficient context for effective use.

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 input schema has 0 parameters with 100% coverage, so no parameters need documentation. The description adds value by specifying that input should be 'an array of up to 1000 numbers,' which provides semantic context beyond the empty schema, earning a baseline score above 3.

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 the tool validates numbers, but it's vague about what 'validate' means (e.g., format, existence, compliance). It distinguishes from siblings by specifying 'up to 1000' numbers, which helps differentiate from validate_up_to_10 and validate_up_to_100, but doesn't clarify the validation criteria or resource type.

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 explicit guidance on when to use this tool versus alternatives like validate_up_to_10 or validate_up_to_100. The description implies usage for bulk validation of up to 1000 numbers, but lacks context on prerequisites, error handling, or comparison with siblings.

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