get_company_jobsList all live job listings for one company (no recency window), newest first. Returns compact summaries; use get_job for full descriptions.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Company slug | |
| limit | No | Results per page (default 20) | |
| cursor | No | next_cursor value from the previous page |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already state readOnlyHint, idempotentHint, and destructiveHint. The description adds useful context beyond annotations: 'no recency window' clarifies the time scope, 'Returns compact summaries' informs return format, and 'newest first' specifies ordering. This enriches the behavioral model without contradicting annotations.
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 concise sentences with no filler. The first sentence states the core purpose, the second adds return format and an alternative tool. Every clause adds 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?
For a simple list tool with full schema parameter coverage and no output schema, the description is nearly complete. It explains the output type and ordering. It doesn't explicitly mention pagination, but the cursor parameter in the schema covers that, so the description is adequate.
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% with clear descriptions for slug, limit, and cursor. The description itself does not add parameter-specific details, but the schema already handles the heavy lifting; baseline 3 is appropriate.
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 a clear verb ('List'), resource ('live job listings for one company'), and scope ('no recency window'). It also mentions ordering ('newest first') and distinguishes from get_job and implicitly from search_jobs by scoping to a single company.
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?
Provides an explicit alternative: 'use get_job for full descriptions.' It implies get_company_jobs is for when you need all live jobs for a company. It doesn't explicitly mention when not to use search_jobs, but the 'for one company' scope offers sufficient context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: company lookup, company-specific jobs, individual job details, job search, trends, salary data, and taxonomy lookups. Even though get_company_jobs and search_jobs both return job summaries, one is scoped to a single company while the other is a global search, making confusion unlikely.
Most tools follow a verb_noun pattern (get_company, get_company_jobs, get_job, list_countries, list_roles, search_jobs), but job_trends and salary_benchmarks are noun compounds without a verb. This is a minor deviation and still predictable, so it's mostly consistent.
With 8 tools, the set is well-scoped for a job data server. It covers retrieval, search, analytics, and reference data without unnecessary bloat or missing essential operations. This is well within the ideal range.
The core workflows—search jobs, get details, company info, trends, salary benchmarks, and filters—are well covered. A notable gap is the lack of a way to discover companies by listing them or searching them, which would make company exploration more complete, but agents can work around this via job search results.