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

Annotations already cover safety (readOnlyHint=true, openWorldHint=false). The description adds real context the annotations don't: that figures are 'typical posted' pay (not actual earnings) and broken into percentiles, plus the national-vs-optional-geographic scoping. It does not discuss caching, rate limits, or sample-size caveats, keeping it out of 5 territory.

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, zero waste. The data shape and output percentiles are front-loaded, with the actionable use case second. Nothing redundant with the schema.

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 no output schema, the description usefully characterizes the return (three percentile values) and the data source ('posted pay'). Combined with full schema coverage, an agent has enough to call the tool correctly; minor gaps like unit/currency assumptions remain.

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 the schema already documents role, metro, state, and specialty with examples and formats. The description only adds high-level meaning (national default, optional geography/specialty), which is useful framing but not detail beyond the structured fields. Baseline 3 is appropriate.

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?

Specific verb+resource: returns quartile hourly pay (25th/median/75th) for a healthcare role with geographic scoping. It distinguishes itself from siblings like get_job, search_jobs, and list_filters by clearly framing the tool as a compensation benchmark.

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?

Explicitly states the use case ('Use it to tell someone whether an offer is competitive'), which gives clear context for invocation. It stops short of naming alternatives or when-not-to-use conditions (e.g., vs. get_job for a specific posting), so it does not reach the top tier.

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