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

With no annotations, the description carries the burden. It identifies the information returned and implies a read-only metadata lookup, but does not disclose whether results are live or static, how sources are identified, or the output format.

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 a single compact phrase with no filler and is front-loaded around the key attributes. It is slightly terse for an agent that may need an explicit operation verb.

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 tool with no output schema, the description gives the essential dimensions (freshness, coverage, known gaps) per data source. It could clarify return structure or scope, but it is sufficient to understand the tool's purpose.

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?

There are zero parameters, so parameter semantics are not a concern and the baseline score is 4. The description does not need to compensate for missing schema documentation.

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 states the resource (each data source) and the attributes exposed (freshness, coverage, known gaps), so an agent can infer it returns source-quality metadata. It lacks an explicit verb and does not distinguish itself directly from siblings, preventing 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 implies the tool is used to assess data reliability and known gaps, but it gives no explicit when-to-use, when-not-to-use, or alternative guidance. For a zero-parameter metadata tool this is adequate but thin.

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