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

Annotations already establish this as a safe, idempotent, closed-world read, so the bar is lower. The description still adds real behavioral content: a hard return cap of 10, a `total` count, the within_days ceiling of 730, the semantic that dates mark when a duty started applying rather than enactment, the note that later phases of an in-force law are marked as such, and the informational-not-legal-advice limit.

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-loaded with the payload description, then when-to-use, then the parameter note, then limits — a sensible order with almost no filler. The single dense opening sentence is long but each clause (ordering, citations, link, guard) conveys distinct information.

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 usefully characterizes what comes back (citation, official link, one-sentence guard, total). However, for a 4-parameter tool at 0% schema coverage, leaving `features` and `jurisdictions` undefined is a material gap an agent would hit on the first filtered call.

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 carry parameter meaning and it only partly does. within_days gets default, maximum, and semantics; limit is only implied by 'Returns at most 10'; and `features` and `jurisdictions` — two of the four parameters — receive no explanation of accepted values or filter behavior anywhere.

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 first sentence names the resource precisely (binding AI-law obligations that started applying recently) and specifies ordering, attached fields, and the one-sentence guard. An agent can tell this is a retrospective 'what just took effect' tool, which implicitly separates it from coming_into_force, though no sibling is named explicitly.

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?

An explicit 'When to use' clause covers three concrete question shapes: what took effect recently, when the newest AI law in a market began applying, and what changed this year. It gives no exclusions or pointers to siblings such as coming_into_force or search_laws, so routing between overlapping tools is left to inference.

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