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create_job_hunt

Create a new job hunt to start tracking and applying to jobs. A job hunt defines what jobs you want to find based on titles, locations, skills, salary, etc. You need at least one job hunt to use match_jobs or add_job_to_applications.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesA name for this job hunt (e.g., "Senior Engineer roles in SF")
configYesSearch filters configuration
autoModeNoEnable full autopilot mode (default: false). When enabled, jobs are automatically matched, scored against your resume using AI, and applied to if they meet your minMatchScore threshold. Resume customization (if enabled) is applied before each application. Each auto-apply consumes a credit.
dailyLimitNoMaximum jobs to auto-apply per day (default: 5, max: 100)
minMatchScoreNoMinimum match score for auto-apply (0-1). Jobs below this score will not be auto-applied. Default is 0.70 (70%) when not explicitly set.
customizeResumeNoEnable AI resume customization for applications (default: false)

TDQS

A3.8/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Since no annotations are provided, the description carries the full burden of behavioral disclosure. However, it only says 'Create a new job hunt' without mentioning side effects, permissions, idempotency, or return value behavior. It does not elaborate on what the creation implies beyond the definition, leaving a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loaded with the primary action, then explaining the concept and prerequisite. Every sentence contributes to understanding the tool's purpose and usage without extraneous detail. This is concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (nested config object, multiple filter parameters), the description provides essential context about what a job hunt is and the prerequisite relationship with other tools. While it doesn't explain the config structure, the schema covers that in full detail. The description is sufficiently complete for its role, though it could optionally add notes about autoMode or credit consumption, but those are already in the schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already thoroughly documents all parameters. The description's mention of 'titles, locations, skills, salary, etc.' adds no new semantic information beyond what the schema provides. Thus, the baseline score of 3 is appropriate; the description neither detracts nor adds meaningful parameter detail.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Create' combined with the resource 'job hunt', clearly stating the tool's purpose. It also differentiates from sibling tools by explaining that a job hunt is a prerequisite for match_jobs and add_job_to_applications, which provides context on how this tool relates to others.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool: when starting a new job hunt, and explicitly states that at least one job hunt is needed before using match_jobs or add_job_to_applications. It does not explicitly mention alternatives or exclusions, but the dependency information gives solid usage guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.7/5.0
Disambiguation5/5

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.

Naming Consistency5/5

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.

Tool Count2/5

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.

Completeness5/5

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.

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