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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), but the description adds real behavior: a hard cap of 10 companies, omission of companies with too few submissions, USD normalization, and a free-tier limitation on the metric. It stops short of describing pagination or what happens when a country has fewer than 10 qualifying companies.

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 output shape and metric are front-loaded and the operational constraints follow in a logical order. The 'Free limit' sentence largely restates the p50-median scope already given in sentence one, so it is slightly redundant, but overall the text is dense and earns most of its space.

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 read tool with no output schema, the description supplies the return shape (up to 10 companies with their median), the exclusion rule for low-submission companies, and the slug-resolution prerequisite. The only gap is the exact response structure and behavior when fewer than 10 companies qualify.

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 both parameters already have documented meaning and examples, establishing a baseline of 3. The description adds the useful 'canonical slug, never guess' rule, but it also lists locationSlug(s) and companySlug(s), which are not parameters of this tool, creating mild noise rather than added precision.

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 first sentence gives a specific verb and resource (top-paying companies), the scope (one job family, one country), the ranking metric (median p50 yearly total comp in USD) and the result cap (up to 10). This is clearly distinguishable from siblings such as get-company-levels or search-companies, which return entity records rather than a ranked compensation leaderboard.

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?

It states explicit prerequisites and routing: resolve names first with search-job-families, search-locations and search-companies, and never guess a slug. It also declares what the tool does not cover (no sample size, level, or years-of-experience filter), which tells an agent when to reach for a more granular sibling instead.

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