Look up a company

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

Annotations already declare idempotentHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. However, the readOnlyHint=false combined with the schema's wait_seconds parameter signals asynchronous job creation that the description never mentions — it does not say results may come back as a job id rather than data, nor how batching across the companies array behaves. That is a meaningful behavioral gap for a lookup tool.

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?

A single dense sentence that front-loads the returned data and then the accepted input forms. No filler or repetition. It is a fragment rather than a full sentence, but nothing wasteful is included.

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?

With no output schema, the description usefully enumerates the returned fields, which compensates partly. But it omits the asynchronous job semantics implied by wait_seconds and the id-return behavior, which an agent calling a batch lookup tool would need to handle responses correctly.

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% and each parameter is documented (including the enum for lookup_by and the default for wait_seconds), so the schema carries the weight. The description's listing of domain/LinkedIn/name mirrors the enum values already in the schema, adding no syntax or format detail beyond it.

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 names the resource (company data) and enumerates the specific fields returned (size, industry, location, website, LinkedIn), so an agent knows exactly what it gets back. It also states the three accepted input key types. It stops short of explicitly distinguishing itself from siblings like enrich_linkedin_profiles or find_decision_makers, but the resource is different enough to be distinguishable.

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 by the accepted lookup keys (domain, LinkedIn URL, name), which tells the agent what inputs are valid, but there is no explicit when-to-use guidance and no mention of when to prefer a sibling such as enrich_linkedin_profiles. Adequate but leaves routing to inference.

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