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

No annotations are supplied, so the description carries the burden; 'Read this' implies a non-destructive read and it discloses the returned fields, which is genuinely useful. It says nothing about whether the values are static, how often they change, or any access constraints — acceptable but not rich for a zero-parameter metadata call.

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?

Two sentences, both earning their place: the first enumerates the returned content, the second states the use case. Front-loaded with the tool's data, no filler.

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 output schema, the description must describe returns, and it does list the four fields an agent will receive. For a zero-param read tool this is essentially complete, though it could note that values are read-only metadata rather than live data.

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, so there is nothing for the description to disambiguate; per the baseline this scores 4. The description correctly implies a single fixed dataset target, avoiding any false impression of parameterisation.

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 exact payload returned — source, computation date, licence, citation — and ties it to a specific dataset (Procedure Cost Checker). It is clearly distinguishable from siblings like dataset_columns or dataset_stats, though it reads as a list of return fields rather than a crisp verb+resource statement.

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?

'Read this to attribute a figure correctly' gives an implied usage context (citation/attribution), but it never states when to prefer this over other metadata tools nor any exclusions. The trigger condition is suggestive rather than explicit.

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