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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds meaningful context by explaining that fulltext_coverage indicates how many items have searchable full text and warning about interpreting keyword counts, making the data quality caveat transparent.

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 two sentences, front-loaded with the core purpose, and the second sentence adds a critical caveat without any fluff. Every word earns its place.

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?

With no parameters and good annotations, the description covers the essential context: what the tool returns and how to use the fulltext_coverage metric. It does not enumerate every statistic, but the output schema exists, so that detail is not required. The warning adds completeness.

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 has zero parameters, so the baseline is 4. The description does not mention parameters, but none exist, and the schema is empty. The focus on output semantics is appropriate and adds value.

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 returns 'Overall statistics for every IWAC subset', which is a specific resource and scope. It highlights a key field (fulltext_coverage), but does not explicitly differentiate from sibling tools like get_newspaper_stats or get_temporal_distribution, so it falls short of a 5.

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 a clear usage context: 'Read that before treating any keyword count as a full-text census.' This tells the agent when this tool is useful. However, it does not mention alternatives or when not to use it, so it lacks explicit exclusions.

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