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

Annotations already cover the safety profile (readOnlyHint, openWorldHint), so the bar is lower. The description adds genuine, non-obvious context about provenance and staleness ('merged from community job lists and refreshed a few times a day'), but omits the server-side paging ceiling and any rate/result-count behavior.

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 sentences, zero filler: scope and data source lead, filtering capability follows. Every clause carries information an agent needs to decide whether to call the tool.

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 need not explain return values, and 100% schema coverage handles the parameters. The main residual gap is explicit differentiation from the same-family search_jobs tool, which the agent must infer from the 'abroad' framing.

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 100%, so each of the four parameters is already documented, including both enums and the 1-based page default. The description's 'keywords, level/region, and field' phrasing only loosely restates those fields and adds no format or edge-case detail.

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?

States a specific verb and resource ('Search internships and new-grad roles abroad') with explicit scope ('mostly USA, some international'), so the agent knows exactly what corpus is queried. It never names the sibling search_jobs, however, so the boundary between global and non-global search is left to inference.

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 filter sentence ('filter by keywords, level/region, and field'), which maps loosely onto query/type/category. No when-to-use, when-not, or alternative routing versus search_jobs, list_job_filters, or get_job is stated.

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