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; the description adds determinism, pagination behavior, and the citation-URL return shape. It still omits result-count limits or empty-result behavior, keeping it below a 5.

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?

Four tight sentences, front-loaded with the core action and filters before the return/behavioral clauses. No filler, though the determinism sentence is somewhat marginal given the idempotentHint annotation.

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 correctly covers return shape (paginated list with permanent citation URLs). The only gap is guidance against the closest sibling, lookup_regulation, which an agent facing both tools would need.

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 100%, so the schema already documents every parameter including defaults and enums. The description's filter list adds consolidation but no new syntax or format detail beyond the schema, so the baseline 3 applies.

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 (search) and resource (Magist's regulation corpus) and enumerates the filter dimensions, so the scope is unambiguous. It does not explicitly distinguish itself from the sibling lookup_regulation, which likely retrieves a single known regulation, so it stops 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 closing sentence gives a clear when-not ('discovery, not a determination of which regulations apply to a specific product'), which implicitly routes determination-style questions to compute_requirements. It does not name any sibling outright or state prerequisites, so it is strong context without full alternative routing.

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