fetchRetrieve the full JobYap document for a search result id: the complete posting as markdown (description, salary, locations, apply link) plus top community comments, with a citable URL.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | A result id returned by search. |
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| url | Yes | ||
| text | Yes | ||
| title | Yes | ||
| metadata | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark this as read-only and non-destructive. The description adds that the output is markdown including specific fields and top comments with a citable URL, providing useful behavioral expectations beyond the safety flags. It does not contradict any annotation.
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, information-dense sentence that front-loads the action and resource, then enumerates the return contents. Every phrase adds value and no words are wasted, making it highly concise and well-structured.
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 fetch tool with one parameter, an output schema, and read-only annotations, the description covers the purpose, input provenance, and output composition sufficiently. It gives an agent everything needed to decide when to use it and what to expect, without requiring the output schema to explain return values.
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 sole parameter 'id' is fully documented in the schema as 'A result id returned by search.' The description reiterates this context but adds no new format, constraints, or examples. Since schema coverage is 100%, a baseline score of 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 uses the specific verb 'Retrieve' and identifies the resource as 'the full JobYap document for a search result id,' listing the contents (markdown of posting plus comments, citable URL). This clearly distinguishes it from siblings like get_job or get_job_comments, which focus on narrower subsets.
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 states the context: given a search result id, you get the full document. However, it does not explicitly mention when to prefer this over get_job or get_job_comments, nor any exclusions, so it lacks direct comparison to alternatives.
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.