job104_apply_analysis

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

With no annotations, the description carries the full burden, and it does disclose real behavior: results come from an internal statistics API plus a reverse-derivation algorithm, so figures are estimates rather than authoritative counts, and no browser is launched. It stops short of failure modes — what happens below the 30-applicant threshold, whether results are cached, rate limits, or auth needs.

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?

It is a single sentence, but the lead is hype ('免啟動瀏覽器！獨門絕技') rather than the resource being analyzed, pushing the actual capability into the middle. The parenthetical justifications add promotional weight without operational value.

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?

An output schema exists, so return values need no explanation, and the description adequately conveys the analysis scope. However, for a tool with zero annotation and zero parameter documentation, the definition leaves gaps around invalid/expired job IDs and the reliability of the derived applicant count.

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% and the description never mentions the single required parameter, so it adds no meaning beyond the self-explanatory field name 'job_url_or_id'. The only implicit constraint — that the input is a 104 job posting — must be inferred from the surrounding prose rather than stated.

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 specifies concrete outputs for a job posting: an inferred real applicant count, competitor education/seniority distributions, and a Top 10 skills list. That distinguishes it from siblings like job104_job_detail (raw posting fetch) or job104_search, though the framing is promotional ('獨門絕技') rather than a clean verb+resource statement.

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?

There is no when-to-use guidance at all: no statement of when to call this instead of job104_job_detail, no prerequisite (e.g., must have a valid posting URL or ID), and no exclusions such as closed or expired postings. The agent must infer the use case from the output list alone.

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