Trigger auto-apply for a job application. This will automatically fill and submit the job application form. You can optionally specify a specific resume to use for this application.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The application ID to auto-apply for | |
| resumeUri | No | Optional: The URI of a specific resume to use for this application. Get this from list_resumes or upload_resume. If not provided, the primary resume will be used. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full behavioral burden. It discloses the core action (fill and submit) but omits important traits: this is a write action with external side effects, likely irreversible, may consume credits (given get_credits sibling), and could fail silently. No reversibility, permission, or failure information is given.
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 sentences, front-loaded with the main verb. It is concise but slightly redundant: 'Trigger auto-apply' and 'automatically fill and submit' say essentially the same thing. Still, no waste and easy to scan.
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 2-param tool with no output schema or annotations, the description covers the main action and optional resume parameter. However, it lacks context on mutation consequences like finality, credit usage, or success/failure reporting. Adequate but with clear gaps for an action with external side effects.
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 has 100% coverage, providing baseline 3. The description adds extra value beyond schema: it explains where to get resumeUri ('from list_resumes or upload_resume') and the default behavior when it's not provided ('the primary resume will be used'). This enriches parameter understanding.
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?
Description clearly states the tool triggers auto-apply for a job application, explicitly saying it 'will automatically fill and submit the job application form'. This specific verb+resource distinguishes it from siblings like add_job_to_applications or search_jobs.
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?
Usage is implied: you use this when you want to auto-apply. However, it does not explicitly state when not to use it or contrast with alternatives like add_job_to_applications, nor does it mention prerequisites or side effects. Only resumeUri guidance hints at parameter sourcing.
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.
