Use after search_jobs when the user picked one job. Pass that job's url from search_jobs (or its slug). Do not use this to search. Plain-text description. No employer apply URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | The theyond.com job URL from search_jobs. Prefer this. | |
| slug | No | Job slug from search_jobs. Use if you don't have the URL. |
Changes observed during successful MCP inspections.
Input schema / properties / slug / descriptionPrevious value: -"Job slug or theyond.com job URL"New value: +"Job slug from search_jobs. Use if you don't have the URL."Input schema / properties / urlAdded value: +{
+ "description": "The theyond.com job URL from search_jobs. Prefer this.",
+ "type": "string"
+}Input schema / requiredRemoved value: -[
- "slug"
-]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is already covered. The description adds behavioral context by specifying the return format ('Plain-text description') and the absence of an apply URL, which is useful for setting agent expectations. However, it does not go into depth about other behaviors like rate limits or pagination, but given the annotations, the description adds reasonable value.
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, with three sentences, and front-loads the key usage context ('Use after search_jobs'). It avoids unnecessary detail and each sentence adds value. It loses a point because it could be slightly more structured by explicitly naming the sibling, but overall it is efficient.
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 tool with two optional parameters printable in the schema and an output that is a plain-text description, the description covers the essential usage context (when to use, what to pass, what to expect) sufficiently. It could mention error handling or what happens if neither parameter is provided, but given the tool's simplicity and annotation coverage, it is nearly complete.
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 schema already describes both parameters in detail (url and slug) with clear guidance on preference. The description reinforces the preference for url over slug and emphasizes that they come from search_jobs, which adds semantic context. Since schema coverage is 100%, a baseline of 3 is appropriate, and the description provides marginal added value.
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 retrieves a single job after search_jobs, distinguishing it from the sibling search tool ('Do not use this to search'). It specifies a single resource (a job) and the context in which it is used (after search_jobs). However, it does not explicitly name the sibling in the purpose statement, though it does refer to 'search_jobs' later.
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 provides explicit usage guidance: 'Use after search_jobs when the user picked one job. Pass that job's url from search_jobs (or its slug).' It also tells the agent not to use it for searching, and clarifies the output (plain-text description, no apply URL). This is clear and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.