Send an outreach email to a recruiter or referrer for a job application. The email will be sent from your configured email.
| Name | Required | Description | Default |
|---|---|---|---|
| body | Yes | Email body content | |
| subject | Yes | Email subject line | |
| contactId | Yes | The contact ID (from get_application_recruiters or get_application_referrers) | |
| applicationId | Yes | The job application ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full burden of behavioral disclosure. It adds the detail that the email is sent from a configured email, but it does not disclose other important behaviors such as irreversibility, potential credit usage, or whether an outreach record is created (implied by the sibling list_outreaches). This is thinner than expected 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 succinct sentences. The first states the core purpose, and the second adds an essential behavioral detail. There is no fluff or 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 with four fully documented parameters, but there is no output schema or annotations. The description omits return behavior, error conditions, and any side effects beyond sending. While the schema covers parameter semantics, the overall context of what happens after sending and any irreversible consequences is missing.
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 description coverage is 100%, with each parameter described, including that contactId comes from specific endpoints. The description itself 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 the action ('Send an outreach email'), the target ('to a recruiter or referrer'), and the context ('for a job application'). This is specific and distinguishes it from sibling tools like apply_to_job, which submits an application rather than sending an outreach email.
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 implies usage as part of the job application workflow ('for a job application') but does not explicitly state when to use this tool vs. alternatives or mention prerequisites. The schema clarifies that contactId comes from get_application_recruiters or get_application_referrers, but this is not in the description itself.
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.
