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

With no annotations, the description must carry the behavioral burden, and it does the important part: it declares this is a read of metadata fields. There is no mention of side effects, format, or permissions, but a parameterless metadata lookup has almost no behavioral surface to disclose.

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, front-loaded with what the tool returns and closed with why to call it. Nothing is padded or 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?

There is no output schema, so the description correctly takes on the job of describing the returned payload, listing all four fields. It stops short of stating the return format (structured vs prose), a minor gap for such a simple tool.

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 schema defines zero parameters, so baseline is 4. The description usefully enumerates the fields returned (source, date, licence, citation), which is the only meaningful semantic content available for a no-input tool.

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 resource it returns: source, computation date, licence and citation for the TelescopeCompareHQ dataset. That content list makes it distinguishable from the other dataset_* siblings, though it never names an alternative to contrast against.

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 a clear, specific condition for use rather than generic filler. It offers no exclusions or named alternatives, but for a zero-param metadata tool the trigger condition is sufficient.

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