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

Annotations already establish read-only, idempotent, non-destrucive behavior. The description adds that the result is a set of work-mode trend buckets, which is useful, but doesn't clarify bucket semantics, time window, or data source. No contradiction.

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?

One short sentence with no filler, front-loading the action and result. Every word earns its place, and the structure is easily scannable.

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 tool is simple (one required parameter, rich annotations), so the description covers the basic call pattern. Yet with no output schema, it doesn't define what a 'trend bucket' looks like, leaving categories, percentages, or time ranges ambiguous.

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%: the role parameter is already documented as 'Role title, for example software engineer.' The description merely repeats 'role title' and adds no extra format, constraints, or edge-case information beyond the 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 uses a specific verb ('Return') and identifies the exact data category (remote/hybrid/on-site trend buckets) and input (role title). This distinguishes it from siblings like jobs_skill_trends by naming the work-mode dimension.

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 phrase 'for a role title' implies the condition for use: when an agent needs work-mode trend buckets for a job title. However, it doesn't explicitily state when not to use it or which sibling like jobs_skill_trends or jobs_momentum should be selected instead.

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