get_job_commentsFetch the community discussion thread for a job: chronological, threaded via parent_id, with like counts. Comments are user-generated content. Threads stay open after a job expires.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Numeric JobYap job id, a full jobyap.com job URL, or a job page slug. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and destructiveHint, and the description adds valuable behavioral context: chronological ordering, parent_id threading, like counts, user-generated content, and that threads persist after job expiration. This goes well beyond the safety metadata.
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 concise, consisting of three focused sentences. Each sentence contributes meaningfully—purpose, data characteristics, and lifecycle behavior—with no redundant phrasing.
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?
Given the simple one-parameter schema and existing annotations, the description provides sufficient context about the response nature (chronological, threaded, like counts). It lacks details such as pagination or explicit return structure, but that is not essential given the tool's simplicity.
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?
The input schema already fully documents the single parameter 'id' with a clear explanation of accepted formats. The description does not add any additional parameter-level detail, so the baseline score of 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?
The description clearly states the verb 'fetch' and the resource 'community discussion thread for a job', explicitly distinguishing it from sibling tools like get_job and get_job_stats. It also specifies key details (chronological, threaded, like counts) that make the purpose unmistakable.
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 description clearly conveys when to use this tool—when you need a job's comment thread—but does not explicitly mention alternatives or exclusionary conditions. This is clear context without being a full when/when-not guide.
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.
There are two overlapping pairs: fetch vs get_job both retrieve job details, and search vs search_jobs both search listings. While the descriptions differentiate them (fetch for search result IDs, get_job for job IDs; search for natural language, search_jobs for structured filters), an agent could easily choose the wrong one without careful reading.
Tool names mix conventions: bare verb 'fetch', 'get_' prefix on three tools, 'list_' prefix, and 'search_' prefix on three others. The pattern is not uniform, though each name does convey its purpose reasonably.
Eight tools is well within the ideal range for a job search server. Each tool covers a distinct facet (search, retrieval, comments, stats, companies, locations) and none feel redundant or extraneous.
The toolkit provides a complete read-only surface for the job search domain: searching, fetching full listings, comments, company list, and location resolution. Minor gaps like per-company detail beyond job count or a direct job-by-ID endpoint could exist, but the core workflow is covered well.