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

With no annotations provided, the description carries the full burden, and it partially meets it by disclosing the returned percentile bands, data point counts, and confidence levels. It says nothing about read-only semantics, data freshness/lag, geographic coverage limits, or pagination behavior even though a per_page parameter exists.

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?

Three sentences, front-loaded with the core operation and followed by return shape then usage context; there is very little waste. The mild overlap between the opening scope sentence and the closing 'specific roles' phrasing is the only redundancy.

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 ten-parameter tool with no annotations and no output schema, the description does the important work of explaining the return payload. It is still thin on the optional dimensions (month, region, company_size, education_level) and on response pagination, which an agent needs to know when constructing a complete call.

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%, so each of the ten parameters is already documented in the schema, making 3 the correct baseline. The description names only four of the ten (role, city, seniority, industry) and adds no format or default guidance for month, region, company_size, macro_industry, education_level, or per_page.

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 uses a specific verb ('Query') plus the resource ('aggregated market salary percentiles') and enumerates the slicing dimensions (role, city, seniority, industry). It does not explicitly contrast itself with closely related siblings such as get_salary_trend or get_stats, but the 'aggregated percentile snapshot' framing makes the distinction inferable.

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 final sentence gives a usage context ('benchmark compensation for specific roles in Chinese and APAC tech labor markets'), which is genuine when-to-use guidance. However, it offers no when-not conditions and never names an alternative, despite siblings like get_salary_trend, get_stats, and calculate_compensation_arbitrage that an agent could easily confuse with this one.

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