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

With no annotations, the description carries the full behavioral burden and does well: it discloses dataset size, that exact matches ignore legal suffixes (LTD/LIMITED/PLC), that active companies are boosted, and that words match as prefixes. It omits pagination/total-count behavior, but the ranking semantics are unusually well specified.

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 sentences, zero filler, with the scope and dataset size front-loaded before the ranking detail. Every clause carries information the agent can act on.

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?

For a two-parameter search tool with no annotations and no output schema, the definition covers purpose, scope, ranking, and return type adequately. It could go slightly further by naming the search_companies alternative or noting result-count/pagination behavior.

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 baseline is 3; the description earns above that by explaining match semantics for 'name' (partial names, legal-suffix-insensitive exact matching, prefix word matching) and by noting the result content. The 'limit' parameter is left to the schema.

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 description gives a specific verb and resource ('Search all UK companies ... by name') and scopes the dataset ('Companies House register, ~5.6M'). It does not differentiate itself from the sibling search_companies, which is a plausible source of confusion, so it falls short of a 5.

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 implied rather than stated: the ranking explanation tells the agent how results are ordered and 'Returns company numbers for lookup_company' chains it to a next step. However, there is no explicit when-to-use/when-not-to-use guidance and no comparison against the sibling search_companies.

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