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update_job_hunt

Update job hunt settings and search filters. Use this to change what jobs are matched. IMPORTANT: When updating config, you must pass the ENTIRE config object as it replaces the existing config (not a partial merge). Use get_job_hunt first to see current config, then include all fields you want to keep.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe job hunt ID
nameNoNew name for the job hunt
configNoSearch filters configuration. REPLACES entire config - include all fields you want to keep.
statusNoJob hunt status
autoModeNoEnable/disable full autopilot mode. 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 (max: 100)
minMatchScoreNoMinimum match score for auto-apply (0-1). Default is 0.70 (70%) when not explicitly set.
customizeResumeNoEnable/disable AI resume customization for applications

TDQS

A4.1/5.0
Behavior4/5

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

The IMPORTANT warning reveals that the config object replaces the entire config, not a partial merge—a critical behavioral trait not otherwise annotated. With no annotations provided, the description carries the burden of disclosing this destructive behavior. It does not mention all possible side effects like credit consumption for autoMode, but those are covered in the schema, and the key risk is clearly flagged.

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 long, each serving a distinct purpose: stating the purpose, issuing a critical warning, and giving a usage instruction. There is no redundancy or fluff; every sentence earns its place.

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 (8 parameters, nested config object), the schema handles parameter documentation thoroughly. The description adds the essential replacement warning and the GET-first workflow. It does not describe the response format, but no output schema exists and the description still provides enough context for a mutation tool.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds value by clarifying that the entire config must be passed and the agent should fetch the current config first, which is essential for correct parameter usage. This goes beyond what the schema's property descriptions state.

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

Purpose4/5

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

The description states 'Update job hunt settings and search filters' with a clear verb and resource, distinguishing it from create_job_hunt and get_job_hunt. However, it is slightly broad because the tool also updates status, autoMode, and other fields that are not strictly 'search filters', but the overall purpose is clear.

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 guidance: 'Use get_job_hunt first to see current config, then include all fields you want to keep.' It gives a practical prerequisite and warns about the full-config replacement. It does not explicitly state when not to use the tool or mention alternative tools for different operations, but the provided instruction is actionable.

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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