Get details of a specific job application by ID. Optionally include the full job listing (description, salary, skills, etc.).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The application ID | |
| includeJobListing | No | If true, includes the full job listing details (description, salary, experience level, skills) in the response |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It states the read operation ('Get details') and the optional expansion, but does not disclose side effects (none expected), permissions, rate limits, or the default response structure. For a read-only getter, this is adequate but not comprehensive.
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 two short sentences with no wasted words. It front-loads the core purpose and then adds the optional modifier. Ideal structure for a simple getter.
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 2 fully described parameters and no output schema, the description covers the essential functionality. Minor gap: it doesn't explain what fields are returned by default or how this relates to specialized getters (e.g., get_application_recruiters, get_application_stats). But the tool is simple enough that the description 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?
Schema descriptions cover 100% of parameters, so the description need not repeat them. It does add value by mapping 'by ID' to the id parameter and 'full job listing' to includeJobListing, but this is redundant with the schema. The baseline 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 clearly uses a specific verb ('Get') and resource ('details of a specific job application by ID'), distinguishing it from sibling tools like list_applications and specialized getters such as get_application_recruiters. The optional job listing detail adds further scoping.
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 context is clear: use when you have an application ID and need its details. It doesn't explicitly mention alternatives or exclusions, but the simplicity of the tool makes the usage obvious. The optional includeJobListing parameter implies when you want more than just base details.
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 targets a distinct resource and action. Tools like get_job vs get_application vs get_job_hunt are clearly separated, and match_jobs vs search_jobs are well-differentiated by saved vs explicit filters. No two tools appear to do the same thing.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., create_job_hunt, list_applications, update_salary). Even longer names like add_job_to_applications maintain the convention with clear, predictable structure.
With 35 tools, the server exceeds the 25+ threshold that indicates an overly large surface. While the breadth covers a comprehensive job search workflow, the number is likely overwhelming and could be consolidated without losing functionality.
The tool set covers the full job hunt lifecycle: creating hunts, searching/matching jobs, applying, tracking applications, managing resumes (including AI-generated versions), outreach, interviews, profile, and compensation. There are no obvious dead ends; update and delete operations are available where needed.
