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import_job_by_url

Import a job from a URL (e.g., LinkedIn, Greenhouse, Lever, Workday) and add it to your applications. Optionally trigger auto-apply immediately. Use this when a user has a direct link to a job posting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe job posting URL (supports LinkedIn, Greenhouse, Lever, Workday, and most ATS platforms)
autoApplyNoWhether to automatically apply to this job (default: false)
jobHuntIdYesThe job hunt ID to add this job to

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description discloses key side effects: adding the job to applications and optionally triggering auto-apply. It clearly signals that this is a mutating operation and highlights the auto-apply behavior, which is essential for the agent's understanding.

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?

Two concise, front-loaded sentences. The first sentence states the action and destination; the second provides a usage condition. No wasted words.

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 moderate complexity (3 parameters, no output schema, no annotations), the description covers the core purpose and key optional behavior. It does not describe the return value, but the main outcome (adding to applications) is clear and sufficient for invocation.

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 description does not need to explain parameter syntax. The description adds context for autoApply ('immediately') that maps to the parameter, but this is marginal. Baseline 3 is appropriate as the schema already documents parameters well.

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 states the exact action ('Import a job from a URL') and the destination ('add it to your applications'), with a specific verb and resource. It distinguishes from siblings like add_job_to_applications by focusing on the URL import mechanism and optional auto-apply.

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?

Provides an explicit usage context: 'Use this when a user has a direct link to a job posting.' This gives clear guidance on when to invoke the tool, though it does not explicitly mention alternative tools or exclusion cases.

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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