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TVLSS

HireJack

Search Jobs

search_jobs
Read-only

Search live tech job postings from 500+ companies. Filter by keyword, role family, seniority, skill, location, salary, remote policy, or visa sponsorship.

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'. Not for a single known posting (get_job), company-level questions (get_company_profile), personalized ranking (recommendations), or aggregate market stats (get_market_pulse).

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 (AI-extracted): 'yes' returns jobs whose posting indicates sponsorship, 'no' those that rule it out. Omit to include jobs where the posting doesn't say.
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.). Omit to search all families.
remoteNoRemote policy filter; 'remote+hybrid' matches either mode. Omit to include onsite jobs too.
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 on the intern → vp ladder. Omit to include all levels.
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_salaryNoSet true to only include jobs with a disclosed salary range; omit to include jobs without pay data.
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.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesSearch results page; meta.next_cursor is present when more pages exist
metaNoRequest/response metadata (pagination cursors, snapshot timestamps, applied filters)
citation_urlNohirejack.com URL to cite when surfacing this result
Behavior5/5

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

Beyond the readOnlyHint annotation (true), the description discloses important behavioral traits: q does not search job descriptions or skill list, pagination via cursor, salary_min/salary_max matching logic, and that results are a slim list with specific fields. No contradictions with annotations.

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 well-organized and front-loaded with the primary action. It efficiently covers purpose, output, examples, and exclusions. Slightly verbose with comma-separated lists but no wasted sentences.

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

Completeness5/5

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

Given 16 parameters and the existence of an output schema, the description adequately covers filtering behavior, return fields, pagination, and edge cases (e.g., salary range matching, q not searching descriptions). It leaves no major gaps.

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

Parameters5/5

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

Despite 100% schema coverage, the description adds significant meaning: explains q's scope limitations, clarifies salary_min and salary_max semantics with examples, describes cursor usage, and provides usage tips for skill and posted_since parameters.

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 the tool searches HireJack's database of live tech job postings, lists filterable attributes, and describes the returned data format. It also explicitly distinguishes from sibling tools like get_job, get_company_profile, recommendations, and get_market_pulse.

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

Usage Guidelines5/5

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

Provides explicit guidance on when to use this tool (for searching tech jobs with various filters) and when not to use it (for single job, company profile, recommendations, market stats). Also gives example queries to illustrate appropriate usage.

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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