Get Rate Benchmark (Rate Index)

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds meaningful behavioral details beyond that: it returns a national typical plus range, handles brand ambassadors by market tier, and describes the optional tier parameter as adding 'tier_usd' data for each role.

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 more detailed than average, but every sentence contributes: scope, data source, return value, example use cases, exclusions, citation, and parameter hints are all covered. It is front-loaded with the core result and the guidance to use alternative tools.

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 tool with two optional parameters, an output schema, and clear annotation coverage, this description is complete. It covers the dataset, measurement scope, tier handling, citation format, and appropriate alternatives. An agent can confidently decide when to invoke this tool and understand the shape of the result before even opening the output schema.

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 parameter basics are already documented. The description adds extra value by explaining what the tier parameter actually does ('adds each role's measured span within that tier (tier_usd)') and by showing concrete example calls with different parameter combinations, which helps an agent understand how to pass arguments correctly.

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 identifies the resource (TempGuru Event Staffing Rate Index) and the specific output: all-inclusive W-2 hourly bill rates by role from 407 markets, with a typical rate plus the national range. It also explicitly distinguishes itself from related tools like get_role_pricing and plan_staffing by stating what the tool is NOT for.

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 guidance is explicit and actionable. It provides example queries, states when to use the tool ('What do event staff cost in 2026?', 'Industry benchmark'), and gives clear exclusions: do not use for one city's price (use get_role_pricing) or to build a budget (use plan_staffing).

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