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

Annotations already declare readOnly, idempotent, non-destructive, so the bar is lower, but the description still adds real interpretive context: the positive TechJobs estimate is from public sources, is explicitly not an official ranking, and a missing label means insufficient public data rather than a negative signal. That caveat prevents an agent from misreading absence as bad news; the only gap is no mention of error behavior for an invalid slug.

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, front-loaded with what the profile contains and ending with the usage recipe; the long field enumeration is dense but each clause maps to actual returned content. The parenthetical caveat is necessary but makes the first sentence a run-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?

With an output schema present, return format needn't be explained, annotations cover the safety profile, and the single parameter is fully documented and reinforced by the description. Nothing an agent needs to call this correctly 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% and the single slug parameter already documents its source and an example ('grab'), so the schema does the heavy lifting. The description restates the slug-acquisition route via search_companies, adding workflow framing rather than new meaning, which fits the baseline 3.

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 a specific resource (a company's profile) and enumerates exactly what it contains: introduction, industry, size, tech stack, open-job count, referral status, and an optional estimate. It also implicitly separates itself from search_companies (slug lookup) and search_jobs (job listings), so an agent can pick the right tool without opening schemas.

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?

Gives an explicit trigger ('Use when the user asks about an employer') plus a two-step routing recipe: obtain the slug via search_companies and enumerate openings via search_jobs (company). Alternatives and their conditions are stated rather than left to inference.

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