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

Annotations already carry readOnly/idempotent/non-destructive/openWorld=false, so the description correctly focuses elsewhere: data provenance (official registries, gazette attributions, congress rosters) and the important caveat that these are internal lookup values, not citable documents. It does not discuss pagination or the 50-match cap beyond what the schema states.

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?

Purpose and the primary use case are front-loaded, and each paragraph has a job. The closing data-sources note is denser than strictly necessary but carries a real citation-hygiene warning rather than 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 an output schema present, the description needn't explain return shape, and it covers the remaining gaps: entity types, id semantics, query strategy, country scoping, and citation caveats. An agent could call this correctly from the definition alone.

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 coverage is 100%, so 3 is the baseline; the description earns more by adding behavior the schema omits — that `country_code` comma-separated and omitting it means all accessible countries — and by illustrating multi-word memory matching that implies broader matching than a plain substring.

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?

Opens with a specific verb+resource ('Returns the full list of government entities') and enumerates the entity kinds covered. It then states the purpose that distinguishes it from list_top_entities and list_regulations: discovering entity_id values.

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?

Explicitly names the downstream tool ('Primary use: discover `entity_id` values to pass to `list_regulations`'), telling the agent both when to call it and what to do with the result. It also explains the query-strategy choice for `q` (name vs acronym vs remembered-name words).

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