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

Annotations already declare readOnly/idempotent/closed-world, so the safety profile is covered; the description instead adds genuine behavioral context the annotations cannot convey — the data_confidence tiers (high = check-digit algorithm vs low = structure only) and the caveat that results are 'structural validation only — never proof that an identifier is issued or belongs to someone'. That disclaimer is real decision-relevant nuance; it loses a point only because much of the enumerated response field list is redundant with the output schema.

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 purpose and scale, then usage routing, then response shape — a sensible ordering with no filler sentences. It is dense, though the trailing enumeration of result fields/data_version/sources runs long for content the output schema already provides.

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?

Covers purpose, cost, the routing relationship to validate_identifier, and the crucial interpretive caveat. Since an output schema exists, the return-value explanation is optional. The one gap is scale handling: with 250+ catalogued codes and two optional filters, nothing says whether results are paginated or return fully unfiltered.

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% and both filters are fully documented in-schema (ISO alpha-2, 'INTL', and the full category list). The description only restates 'filterable by country and category' and adds no format or edge-case guidance beyond what the schema already says. Baseline 3 applies since the schema is doing the heavy lifting.

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 ('Catalogue of the identifier codes this service validates'), gives scale (250+ across 90 countries plus international standards), and explicitly names the downstream sibling it feeds ('Call it once to find the right code for validate_identifier'). An agent can separate it from validate_identifier/detect_identifier without opening any schema.

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?

Clear usage context: 'Call it once to find the right code for validate_identifier' plus the 'Free' cost signal tells the agent this is the cheap discovery step before validation. It stops short of explicit exclusions (e.g. when to skip the catalogue and call validate_identifier directly with a known code), so it is strong but not a full when/when-not pair.

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