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TVLSS

HireJack

Search Jobs

search_jobs
Read-only

Search live tech job postings with filters for keyword, role, seniority, skill, location, salary, remote policy, and visa sponsorship. Returns job title, company, salary range, and key skills.

Instructions

Search HireJack's database of live tech job postings. Filter by keyword, role family, seniority, skill, location, salary, remote policy, or visa sponsorship. Returns a slim list of jobs with title, company, location, salary range, posted date, and key skills. Use this for queries like 'remote senior backend roles paying $200K+', 'data engineer jobs at fintech companies', 'who is hiring Rust developers in NYC'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFree-text keyword search (case-insensitive substring) across raw and standardized title, company name, company domain, and location. Tip: use the `skill` parameter for skill matches — `q` does NOT search job descriptions or the skill list.
visaNoVisa sponsorship: 'yes' or 'no'
limitNoMax results to return (default 25, max 100)
skillNoSingle skill name to require (case-insensitive substring match), e.g. 'Rust' or 'Kubernetes'
cursorNoOpaque pagination cursor from a previous search_jobs call's `meta.next_cursor`. Pass it back (with the SAME filters) to fetch the next page of results.
familyNoRole family (software_engineering, machine_learning, etc.)
remoteNoRemote policy filter
companyNoCompany domain to filter by, e.g. 'stripe.com'
locationNoLocation substring filter, e.g. 'San Francisco' or 'New York'
educationNoMinimum degree the job requires (AI-extracted). E.g. 'bachelor' returns jobs whose stated requirement is exactly a bachelor's.
seniorityNoSeniority level
experienceNoYears-of-experience bucket the job asks for (AI-extracted yearsMin). E.g. '0-2' for entry-level-friendly roles, '10+' for very senior ones.
has_salaryNoOnly include jobs with disclosed salary
salary_maxNoMaximum salary ceiling (annual USD). Matches jobs whose floor is at or below this (i.e. salaryMin <= X).
salary_minNoMinimum salary floor (annual USD). Matches jobs whose disclosed salary range *could pay at least* this much (i.e. salaryMax >= X). A job with range $150K–$250K matches salary_min=200000.
posted_sinceNoOnly include jobs posted on or after this date (YYYY-MM-DD). E.g. for 'jobs posted this week', pass the date 7 days ago.
Behavior3/5

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

Annotations declare readOnlyHint=true, so no contradiction. The description describes what the tool does (search, filter, return slim list) but adds limited behavioral context beyond annotations. It mentions pagination via cursor but doesn't detail other behavioral traits like rate limits, auth requirements, or idempotency. Given annotations provide safety profile, a 3 is appropriate.

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 two sentences plus example queries, all front-loaded with the main purpose. Every sentence is informative with no fluff. It's concise yet covers purpose, filters, return fields, and usage examples.

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 16 parameters and no output schema, the description covers the purpose and filtering capability well. It lists return fields and provides examples. However, it doesn't explain pagination details beyond cursor description in schema, nor error handling. For a complex search tool, it's fairly complete.

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 coverage is 100%, so parameters are fully documented. The description adds value by providing example queries and clarifying that `q` does not search job descriptions or skill lists, which goes beyond the schema description. This additional semantic guidance justifies a 4.

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 clearly states it searches live tech job postings with filtering by multiple dimensions. It includes specific example queries like 'remote senior backend roles paying $200K+' which makes the purpose immediately understandable. It distinguishes from siblings like get_job (single job) and find_companies (company search) through context.

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 example use cases and explicitly notes that `q` parameter does NOT search job descriptions, advising to use `skill` for skill matches. This guides proper usage. However, it does not explicitly state when NOT to use this tool (e.g., for getting full job details) nor list alternative siblings. It's clear but not exhaustive.

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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