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

With no annotations, the description carries the full burden and does real work: it discloses the data provenance and license, the per-call price ($0.25 USDC), and the exact fields returned. It stops short of stating whether name matching is exact or fuzzy, whether `limit` applies to name searches, or what a no-match response looks like — gaps that matter for a paid lookup.

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?

Three tight sentences, front-loaded with purpose and source, then output fields, then copy-pasteable examples, then price. No filler or restatement of the tool name.

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?

The description covers purpose, source, outputs, and cost, and listing return fields compensates for the absent output schema. However, with seven undocumented parameters, no annotations, and no error/no-match behavior, an agent still cannot confidently construct a call without inspecting the schema and guessing at parameter roles.

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% across 7 parameters, so the description must compensate and largely does not: it names only `registration_number` and `name` (via examples) and never explains `q`, `lv`, `number`, `regcode`, or `limit`, nor that several of these appear to be aliases of the same identifier. An agent is left guessing which of the five identifier-ish parameters to populate and what `lv` means.

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 ('Latvian company lookup') plus the authoritative source (Register of Enterprises open dataset on data.gov.lv, CC0) and the accepted identifiers (11-digit registration number or name). The country qualifier cleanly separates it from the ee_/uk_/pl_company siblings, and the returned-field list (legal name, status, legal form, dates, address) tells an agent exactly what it gets.

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?

Usage is only implied: the country scope and identifier formats make it obvious this is for Latvian entities, and two concrete input examples are supplied. But there is no explicit when-to-use versus company_full, company_research, kyb_report, or eu_vat, and no statement of when-not to use it or what to do on a miss.

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