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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false) and openWorldHint=false. The description adds non-obvious behavioral context beyond that: the vocabulary is closed/exhaustive and each entry includes a definition plus a count of cases using it, which tells the agent this is a canonical reference, not a filtered sample.

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?

A single sentence with zero padding, front-loading the key property ('closed vocabulary') and then the payload (definitions + case counts). Nothing redundant.

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 zero-parameter list tool with no output schema, the description supplies the essential return-value context (definitions and usage counts) that would otherwise be missing. It could go slightly further by noting whether counts are filtered or absolute, but it is sufficient to call the tool correctly.

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 tool takes zero parameters, which sets the baseline at 4. No parameter meaning needs to be conveyed, and the description's job is purely to characterize the returned content.

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 names the resource (spread mechanics) and states exactly what each entry carries: a definition and a case-usage count. It is clear what the tool returns, though it never explicitly uses a listing verb or references the siblings get_case/search_cases, so an agent gets no direct differentiation cue beyond the distinct resource name.

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?

There is no explicit when-to-use or when-not-to-use statement and no mention of alternatives. Usage is only implied: calling this to discover the closed vocabulary of mechanics before interpreting or filtering cases. Adequate inference is possible, but the description does no routing work.

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