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

Annotations already declare readOnly, idempotent and openWorld, so the safety profile is covered. The description adds valuable context beyond that: the cost model (free within daily allowance, then $0.003 USDC per call via x402), which is genuinely useful for an agent deciding whether to call. It does not mention rate-limit thresholds or match-quality 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?

Two tight sentences, with the core purpose front-loaded before the pricing detail. Every sentence carries information; the em-dash aside is efficient. Minimal but not wasteful.

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?

An output schema exists, so return shape needn't be described. For a single-parameter matching tool with full annotation coverage, the description covers purpose, use case and cost. The only gap is the absence of explicit sibling routing, which is a minor omission.

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 the single parameter 'q' is documented as 'Approximate name'. The description reinforces this with 'fuzzy matches of a name' and 'messy company names', but adds no syntax, length or formatting guidance beyond what the schema already provides. Baseline 3 is appropriate.

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 operation (fuzzy name matching to LEIs) and the resource, with the quantifier 'Best fuzzy matches'. It implicitly contrasts with exact-match siblings like gleif__search and gleif__autocomplete via 'fuzzy' and 'messy company names', but never names a sibling 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?

The phrase 'for messy company names' does give a condition for choosing this over exact-search siblings, which is better than nothing. However it never names an alternative tool or states when NOT to use fuzzy matching (e.g. clean/known names), leaving the routing largely to inference.

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