greater_than_or_equal

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'checks' a condition, which implies a read-only, non-destructive operation, but does not specify the return format (e.g., boolean, string), error handling for non-numeric inputs, or performance characteristics. The description is minimal and lacks details on what the agent should expect beyond the basic function.

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 extremely concise and front-loaded: a single sentence directly states the tool's function, followed by domain/category tags. There is zero waste or redundancy, and every element (the check operation and context tags) earns its place without unnecessary elaboration.

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 low complexity (simple arithmetic comparison), no annotations, no output schema, and minimal parameters, the description is adequate but incomplete. It covers the basic operation but lacks details on return values, error cases, or usage nuances. For such a simple tool, it meets minimum viability but could be more informative about behavioral expectations.

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% description coverage, but the description compensates by naming the parameters ('first number', 'second number') and clarifying their roles in the comparison. It adds meaning beyond the schema's generic 'a' and 'b' by specifying the semantic relationship (greater than or equal). However, it does not detail data types beyond 'number' or constraints like integer vs. float, leaving some ambiguity.

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 explicitly states the tool's purpose: 'Check if the first number is greater than or equal to the second number.' It specifies the verb ('Check'), the resource (two numbers), and distinguishes it from siblings like 'greater_than' and 'less_than_or_equal' by its exact comparison operation. The domain and category tags further clarify its arithmetic/comparison nature.

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 implies usage for comparing two numbers in arithmetic contexts, but does not explicitly state when to use this tool versus alternatives like 'greater_than' or 'less_than_or_equal'. No guidance is provided on prerequisites, edge cases, or performance considerations. The domain/category tags offer some contextual hint but lack explicit alternatives or exclusions.

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