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

Annotations already cover the safety profile (readOnly, idempotent, closed-world, non-destructive), so the bar is lower. The description adds genuine context beyond them by enumerating what the payload contains, including data-freshness signals (last refresh, refresh frequency) that matter for deciding whether to trust downstream results.

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?

A single front-loaded sentence that immediately answers 'how many' before moving to freshness. It is a long comma-chained list, which reads slightly run-on, but every clause contributes a distinct data point and nothing is padded.

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 zero parameters and an output schema present, the description only needs to convey scope and content, which it does. The one omission is any hint about relative cost or when the aggregate is stale enough to re-call, but that is minor for a trivial stat lookup.

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?

The tool takes no parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. The prose correctly implies the result is unfiltered and global.

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 names the exact data points the tool returns: open job and company counts, number of hiring platforms scanned, last refresh time, and refresh cadence. That is far more specific than the title alone and clearly distinct from get_job/list_job_filters/search_jobs, though it never explicitly contrasts itself with those siblings.

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?

Use is only implied — an agent can infer this is the aggregate/overview call versus the item-level siblings, but the description never says when to prefer it, such as before paging through search_jobs to get scale or freshness. No exclusions or preconditions are stated.

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