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

Annotations already declare readOnly, idempotent, closed-world, non-destructive, so the safety profile is covered; the description adds real behavioral context beyond that. It discloses the derived outputs (percentile span, median, net take-home after federal and state tax, DOL wage level) and scopes them geographically (US tax, US metro wage levels, UK year-only). It does not say what happens on unsupported places or out-of-range pay figures, which holds it at a 4.

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?

It is a single dense sentence with the core computation front-loaded and the output list trailing, so an agent gets the gist immediately. Nothing is filler, but the run-on structure of the enumerated outputs makes it slightly harder to scan than a short bulleted form would be.

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?

There is no output schema, so the description must carry the return-value burden, and it does: it names each returned figure and the conditions under which the DOL wage level applies. With five parameters fully documented in the schema and annotations covering safety and idempotency, nothing an agent needs to call this correctly is missing.

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 baseline is 3, but the description earns more: stating that take-home is computed 'at the midpoint' tells the agent how min and max combine into a single figure, which the schema never says. Framing min as 'the low end of the range, or the only figure' also clarifies that a single number is a valid call. That is genuine meaning added on top of a fully documented schema.

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 states a precise computation: where a given offer or posted range falls on the official pay distribution, returning percentile span, median, US take-home pay, and DOL wage level. That is far more specific than the name alone. It references get_pay only to inherit its place coverage, so the boundary with compare_offers (also a sibling) is never drawn, which keeps it from a 5.

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 implied by the framing ('a job offer's pay, or a posted pay range'), which tells an agent this is for evaluating a concrete figure rather than browsing a distribution. There is no explicit when-to-use/when-not statement and no guidance on choosing between this, get_pay, and compare_offers. The reference to get_pay clarifies shared place coverage but not task selection.

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