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

Adds substantial context beyond readOnlyHint/openWorldHint: the $0.002 USDC per-successful-call cost via x402, the fact failed calls are not charged, and the 999-result cap imposed by XING. It also flags data caveats (posting time only when XING shows it, external partner ads), which materially affects result interpretation.

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?

Front-loads the resource and region before listing returned fields, with pricing isolated in a second sentence. The field enumeration is dense but each element conveys real return-value structure, so little is wasted.

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?

Covers region, inputs, return fields, result cap, and payment model, which is enough for correct invocation; the output schema already handles return structure. Only minor omissions, such as the 20-page pagination limit, are left to the schema.

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 all three parameters (keywords, location, page) are already documented with examples. The description restates keyword/location meaning and adds no syntax or constraint detail beyond the schema, so baseline 3 applies.

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 resource (XING job listings) with explicit regional scope (Germany, Austria, Switzerland) and the query inputs. Against siblings like jobs_indeed or jobs_linkedin_jobs, the DACH/XING focus makes selection unambiguous.

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 "for a keyword and optional location" phrasing implies the query pattern, and the region caveat implies when this board is appropriate, but it never explicitly says when to pick this over another job board or when not to use it. Usage is inferable rather than stated.

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