validator_validate_range

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

The behavior is mostly clear from the description: it checks if a number is within the specified min/max range. However, it does not specify behavior when both min_val and max_val are null, which could be confusing.

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 exceptionally concise with a single sentence and the return type, front-loading the key purpose and result format.

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 tool's simplicity, the description covers the essential purpose and parameters. It lacks edge-case handling (e.g., both bounds null), but overall it provides sufficient context for basic 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?

Schema description coverage is 0%, so the description must add meaning. It mentions min_val and max_val are optional with default null, and describes the return structure. Parameter names are self-explanatory, but no further semantics are added.

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 it validates a number within a range and specifies the return structure. It distinguishes from sibling validators (e.g., validate_email, validate_pattern) by focusing on numeric range 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 does not explicitly state when to use this tool versus alternatives like validate_type or validate_length. It provides no usage context or exclusions, leaving the agent to infer from the tool name.

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