Add a job from search results to your applications. Use this when a user wants to save/track a job they found.
| Name | Required | Description | Default |
|---|---|---|---|
| jobId | Yes | The job ID to add to applications | |
| jobHuntId | Yes | The job hunt ID to add this job to |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only says 'Add' and 'save/track', without revealing side effects (e.g., whether duplicates are created), prerequisites (e.g., existing jobHunt), or return behavior. This is minimal disclosure for a mutation tool.
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 sentences, with the core purpose front-loaded. Every word earns its place, and there is no redundant information.
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?
The tool is simple (2 parameters, no output schema, no nested objects). The description covers purpose and usage, but given no annotations, it omits behavioral details like idempotency, failure conditions, or what happens if the job is already added. This is adequate but with clear gaps.
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 describes both parameters with 100% coverage ('The job ID to add to applications' and 'The job hunt ID to add this job to'). The description adds no additional parameter semantics, so 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 states 'Add a job from search results to your applications', which specifies the verb, resource, and context. It distinguishes from sibling apply_to_job by emphasizing 'save/track', making the purpose unambiguous.
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?
It explicitly says 'Use this when a user wants to save/track a job they found', providing a clear condition for use. However, it does not mention alternatives or exclusions, so it stops short of full guidance.
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.
