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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower, yet the description adds real context: it returns the *live* catalogue, it validates availability before answering, and it carries no question-quota cost. It does not mention rate limits or pagination behavior.

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?

Front-loads purpose in the first clause, then examples, then return shape, then filters, then the quota caveat. Tight overall; the parenthetical example questions are useful but make it longer than strictly necessary.

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 an output schema present, the description needn't detail return values, yet it summarizes them reasonably. For a zero-required-parameter discovery tool the description is nearly sufficient; only the limit parameter handling is left unexplained.

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?

Schema description coverage is 0%, so the description must compensate. It names the filter axes ('industry, jurisdiction or a text query'), covering three of the four parameters, but says nothing about the limit parameter or the array format of jurisdictions, leaving genuine gaps.

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?

States a specific verb and resource ('Lists what RegAffairs AI covers') and enumerates the exact return fields (dataset id, name, regulator, jurisdiction, industry, contents, last refresh). It is clearly distinguishable from siblings like search_regulations and ask_question because it describes a coverage catalogue rather than a lookup or a question.

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?

Gives concrete trigger questions ('do you have the EU Cosmetics Regulation?') and states the operational rule that it 'does not count as a question,' which distinguishes it from regaffairs_ask_question. It does not explicitly name the sibling tool or state when not to use it, so it stops short of a 5.

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