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

It goes beyond annotations by detailing the nature of the data, specifically that an 'unmeasured axis' is a first-class, valid state ('never an error and never a zero'), which is critical behavioral context.

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 dense, but highly effective. The information is front-loaded with the identity of the tool and is structured to explain complex concepts (unmeasured status) logically.

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?

The definition is extremely complete for a complex, zero-parameter tool. It defines not only what the tool is but also the philosophical implications of its output (e.g., gap visibility vs. error state), providing comprehensive operational context.

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?

Despite the input schema being empty, the description explicitly lists seven potential filters (e.g., 'accuracy,' 'family,' 'dates'). This explains the 'semantics' of the data structure even if the tool doesn't currently support them, greatly aiding agent understanding.

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 that the tool represents 'the care axis' of the live GSPC board, clearly defining the resource and its function.

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?

Since the tool takes no arguments, usage guidance centers on what the tool *is* (the axis) and doesn't require external parameters to function. It clearly defines the unique nature of its output.

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