salary_growth_ranking

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

With no annotations provided, the description carries the full transparency burden. It discloses a key behavioral trait—using 'entire available history'—and explains the effect of the ascending parameter on sorting. However, it does not state that the operation is read-only or describe the return format, though the output schema covers that.

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 two lines: a purpose statement followed by a concise Args section. Every element earns its place, and the parameter explanations are directly mapped. There is no verbose or redundant content.

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?

The description covers the core purpose and both parameters, and the output schema is available to document the return structure. It is complete for a simple ranking tool, though it could mention potential edge cases like missing data. Overall, it leaves no major gaps.

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?

The schema provides no descriptions for the parameters, but this description fully compensates by explaining 'limit' as the number of regions to show and 'ascending' as whether to start from smallest or largest growth. This adds clear semantic meaning beyond the bare type declarations.

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 clearly states the tool ranks regions by salary growth in construction over all available history. This is specific and distinct from siblings like salary_history, which provides historical data for individual entities. The purpose is unambiguous despite using a noun phrase rather than a verb.

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 implies usage when a ranking of regions by salary growth is needed, but it does not explicitly contrast this tool with sibling tools like salary_history or list_datasets. There are no exclusions or alternative recommendations, so usage guidance is only implicit.

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