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

The annotations already declare readOnly/openWorld/idempotent/non-destructive, so the safety profile is covered and the description instead adds real behavioral context the agent cannot get elsewhere: the data source (Job Spotter's own index of employer career pages), an explicit sampling caveat ("a large sample, not a count of every job"), the anonymity threshold on search data (10+ searches), and the existence of a ready-to-read summary in the `say` field. That is meaningful disclosure beyond the structured fields; only the absence of any guidance on aggregation period or geographic coverage limits keeps it at 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?

The purpose is front-loaded in the first sentence and the metric list follows, so a skimming agent gets the gist immediately. It is dense and runs long with some near-repetition ("open roles" then "roles added... roles taken down"), but essentially every clause carries content rather than filler.

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 carries the burden of explaining return values, and it does so thoroughly by enumerating the metrics returned and flagging the `say` summary field. The sampling caveat prevents over-reading the numbers. What is missing is any sense of time granularity, pagination, or response shape beyond the metric list.

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% and every parameter already carries an example-bearing description (where, country, function with its enumerated job areas), so the schema does the work. The description's phrase "a split by job area and country" loosely maps to `country` and `function`, but adds no format, default, or combination behavior beyond what the schema states. Baseline 3 is correct here.

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 opens with a specific verb-like framing ("The hiring market right now") and then enumerates exactly what is returned: open roles, week-over-week additions and takedowns, employers adding/cutting, median advertised pay, AI role share, and WARN layoffs. That is far more than a restatement of the name. It stops just short of 5 because it never names a sibling (e.g. jobspotter_job_demand or jobspotter_whats_hiring) as the tool to use for a narrower question, leaving the boundary implicit.

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?

It gives concrete elicitation phrases ("how's the job market?", "is tech hiring picking up?", "is it a good time to look for sales jobs in the UK?") and states an intended role: fresh evidence when advising on where to look. That is clear when-to-use guidance. There are no explicit exclusions or pointers to alternatives, so it falls short of a 5.

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