Find a company

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

Annotations already indicate this is read-only, idempotent, non-destructive, and open-world. The description adds genuinely useful behavior beyond those hints: it returns a shortlist with status, type, and incorporation date; it surfaces a disambiguation_needed flag; and it warns that many live companies share names and that picking the wrong one produces a confident answer about the wrong business. This materially improves the agent's understanding of the tool's 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?

The description is well structured, front-loaded with the core purpose, and every sentence adds decision-relevant value: what it searches, when to use it, what it returns, and how to handle ambiguity. It is moderately long but not bloated, and nothing is 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?

For a search tool with four clearly described parameters, an output schema, and comprehensive annotations, the description covers all the important operational context: when to use it, what it returns, how to disambiguate, and how to handle pagination via the schema-described fields. Nothing critical is missing.

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 100%, with each parameter already documented clearly. The description adds a little extra meaning, such as accepting a trading name and clarifying that disambiguation_needed should drive user interaction, but the schema already carries most of the parameter semantics. 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?

The description states a specific verb ('Search Companies House'), a precise resource ('UK company'), and the accepted input forms (name, trading name, or number). It also explicitly positions this tool as the entry point whenever a name rather than a number is known, distinguishing it from the other tools in the server.

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 description gives explicit guidance: start here when you have a name because every other tool needs the number. It also provides a clear behavioral rule for ambiguous results: ask the user when disambiguation_needed is true instead of blindly taking the first result. This is direct, actionable usage guidance.

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