get_job_detail

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

With no annotations at all, the description carries the full burden and does disclose a genuinely important behavioral trait: the tool only supports a named set of sources (Midas, Samsung, Greeting, Greenhouse including Toss) and signals unsupported sources via supported=False, which the agent should handle by switching to WebFetch. It does not describe response shape, failure modes, or rate/auth behavior, which keeps it short of a 5.

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?

Three short lines: what it fetches, where the argument comes from, then the supported-source matrix and fallback. Nothing is padded. Minor deduction because 'supported=False' is introduced without stating that it is a field in the response, which is not discoverable from the input schema.

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?

There is no output schema and no annotations, so the description must convey enough to call the tool correctly; it covers the input provenance, the source support matrix, and the fallback path. The remaining gap is that the response payload (beyond the supported flag) and the meaning of supported=False relative to the input are left implicit, which could momentarily confuse an agent reading only 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 description coverage is 0% for the single 'url' parameter, so the description must compensate, and it does by naming the exact provenance of the value (a url taken from search_jobs output) rather than just restating that it is a url. That is meaningful semantic guidance beyond the schema, though it does not clarify accepted URL formats for each supported source.

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 states a specific verb and resource ('공고 본문(자격 요건·연차 등)을 API로 가져온다' — fetch the job posting body including qualifications and experience via API) and ties the url to a specific sibling, search_jobs. It is clearly distinct from list_companies, fetch_jobs, and search_jobs, though it does not explicitly contrast itself with fetch_jobs, which is the closest sibling.

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 an explicit entry condition ('url은 search_jobs 결과의 url' — the url comes from search_jobs results) and an explicit alternative path: use WebFetch when supported=False. It does not say when to prefer this over fetch_jobs or what to do if search_jobs returned no url, but the core routing guidance is present and actionable.

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