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).

Fetch one job posting by domain + jobId, or by HireJack detail URL. Returns title, company, location, salary, skills, seniority, posted date, visa/remote/education metadata, and (when available) the AI summary. Use after search_jobs when the user picks a specific role to discuss, or when the user pastes a HireJack job URL. Not for browsing or filtering postings (search_jobs) or personal fit scoring (match_job).

Fetch HireJack's full hiring profile for a single company by domain. Returns: tech stack (top skills with counts), role distribution, seniority breakdown, location breakdown, hiring trend (% MoM), salary medians where disclosed, and an AI-generated hiring brief. Use this for queries like 'what is Stripe hiring?', 'what tech does Anthropic use?', or before comparing companies. Not for historical trends (get_company_history, Analyst) or the user's personal fit (company_fit).

List HireJack's tracked companies with hiring volume. Filter by name/domain (q) or industry. Returns slim records with domain, name, industry, total open jobs, and engineering job count. Use this to find companies in a sector ('which fintech companies are hiring?') or to resolve a company name to its domain before calling get_company_profile. Not for deep per-company data (get_company_profile) or multi-axis segmentation by trend/skill/job-count (find_companies, Analyst).

Get HireJack's market-wide snapshot: total open tech jobs, tracked companies, remote share, top skills by demand, top companies by hiring volume, and trending skills (week-over-week movers). Use for high-level market questions like 'how is the tech job market right now?' or 'what skills are trending?'. Not for history or time-series (get_market_history, Analyst) or job-level search (search_jobs).

Score how well the authenticated user matches a specific job. Pro tier. Returns matchPct (0-100), a dimension breakdown (skills, role, seniority, location, remote — plus experience when both the user's resume-derived years and the job's required years are known), matched/missing/bonus skill lists, an experienceFit comparison, ATS-specific resume tips for the company's ATS, and a priorityScore that factors hiring velocity. Use for queries like 'how well do I match this job?' or 'should I apply?'. Not for company-level fit (company_fit) or discovering new jobs (recommendations).

Score how well the authenticated user fits a company. Pro tier. Returns fitScore (0-100), 5-dimension breakdown (tech stack 40%, roles 25%, seniority 15%, location 10%, hiring trend 10%), matching skills, skill gaps, role alignment, and a hiring-momentum signal. Use for 'is Anthropic a good fit for me?' or 'compare these companies for me'. Not for scoring a specific job posting — use match_job for that.

Get top job recommendations for the authenticated user, scored against their profile (skills, desired roles, seniority, location, remote preference) and hard-filtered by their remote/US-only/minimum-salary preferences. Pro tier. Returns jobs ranked by composite match score with per-job match details (default 10, limit up to 50). Use for 'show me jobs that match me' or 'what should I apply to this week?'. Not for unpersonalized filter searches (search_jobs) or scoring one known job (match_job).

Compare a salary against the live HireJack market for a role family + seniority slice. Pro tier. Returns precomputed P10/P25/P50/P75/P90 percentiles, the user's percentile ranking (when salary is supplied), and a career-ladder progression of medians by seniority. Use for 'am I paid well as a senior backend engineer?' or 'what should I ask for?'. Not for a specific job's posted range (get_job) or market-wide comp stats (get_market_pulse).

Analyze the gap between the authenticated user's current skills and what their desired roles require in the live market. Pro tier. Returns matchPct (0-100), the list of skills the user already has that map to their target roles, and the list of missing skills ranked by impact (how often the skill appears in target-role postings). Use for 'what should I learn next?' or 'how close am I to senior PM roles?'. Not for simulating the payoff of skills the user might LEARN — use skill_impact for that.

Compute the authenticated user's market position score (0-100). Pro tier. Weighted: 50% skill demand against current market, 20% seniority fit, 15% remote availability for the user's preference, 15% skill breadth. Returns score, matchingJobs count, salaryMedian for matching roles, per-skill demand breakdown, and the top companies whose tech stacks align best with the user's skills. Use for queries like 'how do I stack up against the market?' or 'what's my market position right now?'. Not for job-specific (match_job) or company-specific (company_fit) scores.

For each skill the authenticated user does NOT have, simulate adding it and compute the market impact. Pro tier. Returns a ranked list of skills with: newJobsUnlocked (jobs that previously didn't match but would after learning the skill), boostedJobs (existing matches that would score higher), companiesNeedingIt, relevantRoles, and a composite impactScore. Also returns profileCompleteness so the caller can suggest filling missing profile fields. Use for queries like 'what should I learn next?' or 'which skill would unlock the most jobs for me?'. Not for auditing the user's CURRENT skills against their target roles — use skill_gap for that.

Aggregate hiring intelligence on every company the authenticated user is watching. Pro tier. For each watched company returns: totalJobs currently open, hiringTrend (up/down/stable), trendPct (week-over-week %), topSkills the company is hiring for, medianSalary, sparkline data (last ~12 weeks of job counts), and jobDelta since the previous snapshot. Use for queries like 'what's happening at the companies I'm watching?' or 'which of my watched companies are scaling up right now?'. Not for a plain list of watched companies — use list_watchlist for that.

Generate targeted resume bullet rewrites for a specific job, using the user's uploaded resume + the job description as context. Premium tier. Returns before/after bullet rewrites, missing keywords from the JD, and ATS-format tips. The user must have a resume uploaded to HireJack (via Settings or Onboarding). Use for 'rewrite my resume for this Stripe role' or 'tailor my bullets for this JD'. Not for interview preparation — use interview_prep for that.

Generate targeted interview prep for a specific job: 5 key topics (deep vs surface depth based on job seniority), 5 likely questions by type (technical, behavioral, system design) with answer tips, and 3 company-specific research items. Premium tier. Uses job description + company tech stack + user skills as context. Use for 'help me prep for my Anthropic interview' or 'what should I expect in this loop?'. Not for resume tailoring — use resume_rewrite for that.

Time-series of a company's hiring profile. Analyst tier. Returns monthly snapshots (totalJobs, engineeringJobs, medianSalary, hiringTrend, trendPct, top skills, seniority + family distribution) plus the wider monthlyPostings job-count series and current-state summary. Use for 'how has Anthropic's hiring changed since January?' or 'is Stripe growing or shrinking?'. Not for a current-state snapshot (get_company_profile) or side-by-side comparison (compare_companies).

Time-series of a skill's market adoption. Analyst tier. Returns monthly companyCount + jobMentions for the skill, top companies hiring for it each month, and computed MoM deltas. Use for 'how fast is Rust adoption growing?' or 'is React still dominant?'. Not for discovering early-stage skills you can't yet name — use find_emerging_skills for that.

Time-series of market-wide hiring stats: total jobs, remote share, compensation, seniority + family distribution, top skills. Analyst tier. Daily resolution back to early March 2026; monthly resolution from March 2026. Use for 'how has the market shifted in 2026?' or 'is remote hiring trending up?'. Not for the current snapshot — use get_market_pulse for that.

Compare hiring profiles of multiple companies side-by-side. Analyst tier. tier. Returns per-company current state (totalJobs, medianSalary, trend, top skills) plus monthly snapshot history for the chosen window. Up to 5 companies. Use for 'compare hiring at Stripe vs Plaid vs Adyen' or 'which of these is growing fastest?'. Not for one company in depth (get_company_profile) or the user's personal fit (company_fit).

Multi-axis company segmentation. Analyst tier. Filter by industry, role family they're hiring for, top-skill match, hiring trend, job-count range. Returns companies sorted by total open jobs descending. Use for 'fintech companies hiring ML engineers', 'defense tech companies scaling up', or 'who's hiring 100+ engineers and growing?'. Not for a simple name or industry lookup — use search_companies for that.

Companies with extreme hiring growth right now. Analyst tier. Returns companies whose computed trendPct exceeds the threshold (50% by default), sorted by growth descending, with their recent monthly job counts. Use for 'who's scaling fastest right now?' or 'find companies doubling their hiring'. Useful for investors and recruiters tracking momentum. Not for custom-axis segmentation by industry/family/skill — use find_companies for that.

Skills with low-but-consistently-growing market adoption — early-stage signals. Analyst tier. Tracks companyCount across the last 3 monthly snapshots and surfaces skills that climbed consistently (non-decreasing) from a low base, with a meaningful absolute company-count gain — not just a big percentage on a tiny base. Use for 'what skills are quietly trending?' or 'what should I learn before everyone else?'. Defaults: adoptionMin 5, adoptionMax 25, growthMin 30%, minDelta 4, baseMax 8, limit 20. Returns a deliberately tight list; loosen minDelta / baseMax / growthMin to widen it. Not for trend lines on an established, named skill (get_skill_history) or role-level emergence (find_emerging_roles).

Job roles gaining company adoption — which titles are spreading across the market. Analyst tier. Compares each canonical role's company count today against a daily rollup snapshot windowDays ago (default 21) and returns roles that cleared the growth thresholds, plus genuinely NEW titles the classifier just started seeing (how 'Forward Deployed Engineer' was first caught). Use for 'what roles are companies suddenly hiring for?' or 'is the AI-engineer title spreading?'. Defaults: windowDays 21, minCompanies 5, minDelta 2, growthMin 25%, limit 20. Not for skill-level signals — use the companion find_emerging_skills for those.

Save a job to the authenticated user's saved-jobs list on HireJack (or remove it with action='unsave'). Saved jobs appear at hirejack.com/saved.html and feed batch match scoring. Idempotent — saving an already-saved job is a no-op. Use when the user says 'save this one', 'bookmark these three', or 'remove that from my saved jobs'. Not for tracking an actual application (track_application) or following companies (watch_company).

Add a company to the authenticated user's watchlist on HireJack (or remove it with action='unfollow'). Watched companies power watchlist_intelligence, daily job alerts, and the weekly digest. Idempotent — following an already-watched company is a no-op. Use when the user says 'watch this company', 'follow Stripe for me', or 'stop watching them'. Not for saving individual job postings — use save_job for that.

Track a job application in the authenticated user's pipeline on HireJack — mark a job applied, advance its stage (applied → phone_screen → interview → offer / rejected / withdrawn), attach notes, or un-track it with remove=true. Powers the Kanban pipeline at hirejack.com/saved.html. Use when the user says 'I applied to this', 'move Stripe to interview', or 'log that I got an offer'. Not for mere bookmarking without applying — use save_job for that.

List the authenticated user's saved jobs on HireJack, newest first — the read companion to save_job. Returns title, company, ids (reusable with get_job/match_job/save_job), and flags for postings that have since closed. Use when the user asks 'what jobs have I saved?' or wants to review/prune their shortlist. Not for application-pipeline status — use list_applications for that.

List the authenticated user's tracked job applications with their pipeline stage (applied / phone_screen / interview / offer / rejected / withdrawn), newest first — the read companion to track_application. Use when the user asks 'what's in my pipeline?', 'where did I apply?', or before moving an application to a new stage. Not for the saved/bookmarked list — use list_saved_jobs for that.

List the companies on the authenticated user's HireJack watchlist — the read companion to watch_company. Returns company name, domain (reusable with get_company_profile/company_fit/watch_company), and follow date. Use for 'what companies am I watching?' or before adding/removing one. Not for per-company hiring trends and stats — use watchlist_intelligence (Pro) for that.

Get the authenticated user's HireJack profile: skills, desired roles, tier, and the matching preferences (seniority, city, remote, US-only, minimum salary) that hard-filter their recommendations, For You feed, and email alerts. Call this before explaining match results or recommendations — a minimum-salary floor or remote-only preference changes what the user sees. Not for changing preferences — use the companion write tool update_preferences for that.

Update the authenticated user's HireJack matching preferences: minimum salary (USD), require-listed-salary strict mode, remote preference, US-only, target seniority, preferred city. Changes persist to the user's profile and immediately re-filter their For You feed, recommendations, weekly digest, and daily job alerts — same effect as editing Settings on the website. Returns the full updated preference set. Use for 'raise my minimum salary to $150K', 'only show me remote US jobs', 'set my target level to staff'. Not for reading current settings — use get_profile for that.