validate_data

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It doesn't disclose whether validation is strict or lenient, what happens on failure (e.g., returns boolean vs error), performance characteristics, or rate limits. 'Validate' implies a read-only check, but details are lacking.

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, efficient sentence that front-loads the core purpose and enumerates all supported formats. Every word earns its place with zero redundancy, making it easy to scan and understand quickly.

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?

For a validation tool with 2 parameters, 100% schema coverage, and no output schema, the description is adequate but incomplete. It covers what formats are supported but lacks details on return values, error cases, or validation specifics. Given the simplicity, it meets minimum viability but leaves gaps an agent would need to infer.

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 parameters 'input' and 'type' are well-documented in the schema. The description adds value by listing all possible validation types, but doesn't explain parameter interactions or validation rules beyond what the enum provides. Baseline 3 is appropriate given high schema coverage.

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 data against various formats' with a comprehensive list of supported formats. It specifies the verb (validate) and resource (data), though it doesn't explicitly differentiate from siblings like 'analyze_language' or 'format_json' which serve different purposes.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, error handling, or compare it to similar tools like 'format_json' or 'decode_base64' that might overlap in functionality. Usage context is implied but not explicit.

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