City employee pay statistics

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so safety is covered. The description adds genuinely new behavioral facts beyond that: results are pre-aggregated, default to the latest quarter, and individual employees are explicitly not listed (a privacy/scope constraint). Rate limits or auth requirements are still unstated.

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 short sentences, front-loaded with what the tool returns, and no filler. The parenthetical defaults are efficiently embedded rather than spread across extra sentences.

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 an output schema present, return values need no explanation, and the annotations carry the safety profile. The remaining gap is the under-documented limit and year parameters and the unspecified interaction between department and job_title filters, which an agent would need before refining a query.

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 only 33% (just job_title and department), so the description must compensate. It partially does: it names the group_by alternatives and states quarter defaults to the latest. It adds nothing on year, limit (default 25, max 100), or how department and job_title interact when both are supplied.

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?

Names a specific resource and the exact outputs (head count, annual pay rates) plus the aggregation granularity (department or job title, one quarter), so an agent knows precisely what it gets back. It does not distinguish itself from sibling data tools like query_dataset or search_datasets that could plausibly return the same underlying data.

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 is only implied: 'aggregated by department or job title for one quarter (the latest by default)' tells the agent the tool's shape but never states when to pick this over query_dataset/describe_dataset or what conditions make it inapplicable. No explicit when/when-not guidance is given.

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