get_job
Full details for one job (description, qualifications, salary, metadata) by job_id from search_jobs.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes |
Full details for one job (description, qualifications, salary, metadata) by job_id from search_jobs.
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the return content (description, qualifications, salary, metadata) which is useful. It does not explicitly state it is read-only or mention error cases, but 'get' strongly implies a safe retrieval operation, and the listed content adds transparency beyond the schema.
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?
The description is a single, front-loaded sentence conveying purpose, content, and parameter source without redundancy. Every word earns its place.
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?
For a simple tool with one parameter and no output schema, this description is complete: it states what it does, what it returns, and how to obtain the required parameter. The sibling relationship is also clarified.
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%, so the description must compensate. It clearly explains the job_id parameter's purpose (identifies the job) and its origin (from search_jobs), adding semantic value that the raw schema lacks.
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 clearly states the tool fetches full details for one job, listing specific content categories (description, qualifications, salary, metadata). It distinguishes from the sibling search_jobs by focusing on a single job by ID.
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 phrase 'by job_id from search_jobs' explicitly conveys the workflow: use search_jobs to obtain a job_id, then call get_job for full details. This differentiates it from the sibling and clarifies when to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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