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update_profile

Update your job seeker profile with personal details, skills, experience, and work preferences to ensure recruiters see current information.

Instructions

Update your user profile fields

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
genderNoGender
skillsNoList of skills (e.g., ["Python", "JavaScript", "AWS"])
headlineNoProfessional headline (e.g., "Senior Software Engineer at Google")
lastNameNoYour last name
locationNoYour location (e.g., "San Francisco, CA")
ethnicityNoEthnicity
firstNameNoYour first name
experienceNoYears of experience
phoneNumberNoPhone number without country code (e.g., "4084586677")
phoneCountryIsoNoISO country code for the phone number (e.g., "US", "IN")
noticePeriodDaysNoNotice period in days (0-180)
openToRelocationNoWhether you are open to relocating for a job
phoneCountryCodeNoPhone country dial code with + prefix (e.g., "+1" for US, "+91" for India)
workPermitLocationsNoCountries where you have work authorization, as ISO country codes (e.g., ["US", "CA", "GB"])
immigrationSponsorshipRequiredNoWhether you require immigration/visa sponsorship (e.g., H1B)
Behavior2/5

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only repeats the action ('Update your user profile fields') without explaining whether it's a partial update, whether it modifies the authenticated user's profile exclusively, or any side effects. This is inadequate 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.

Conciseness4/5

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

The description is a single concise sentence that is front-loaded and free of fluff. It is appropriately short for a tool whose parameter details are fully documented in the schema, though it borders on under-specification.

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

Completeness2/5

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

With 15 parameters and no output schema, the description is incomplete. It fails to mention that all parameters are optional, that only provided fields will be updated, or what the response contains. This is a significant gap for a tool of this complexity, making it much less useful than it could be.

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%, meaning all 15 parameters have detailed descriptions in the input schema. The tool description itself adds no parameter semantics, but since the schema already covers them, the baseline of 3 is appropriate.

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 clearly states the tool's purpose with a specific verb ('Update') and resource ('user profile fields'). It distinguishes from siblings like get_profile (read-only) and update_salary (salary-specific). However, it lacks detail on which fields are included, leaving that to the schema.

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

Usage Guidelines2/5

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

There is no explicit guidance on when to use this tool or when to prefer alternatives. It does not mention exclusive conditions, prerequisites, or a note like 'Use update_salary for salary changes.' The usage context is only implicitly derived from the tool's name.

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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