claude

jobclaw-skills

JobClaw by whatNxtAI — end-to-end job-hunt Agent Skills (bring your own keys; most need none).

7 on GitHubby Jeevesh Jainv0.2.1MITupdated 5 months agoproductivity
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Plugin jobclaw-skills from marketplace jobclaw-skills in jain777/jobclaw-skills. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (20)

  • answer-application-questions

    Answer one or many application-form questions from the master profile, obeying per-type format rules — numeric → number only, yes/no → Yes|No, short → ≤ 2 sentences, paragraph → ≤ max_chars, enum → one of options. Batch JSON in/out (for JobClaw form-fill); single-question paste mode for interactive

  • apply-to-job

    Orchestrate the full apply chain for one job — capture the job once, score fit, tailor the resume (PDF), write the cover letter, and answer the application questions — in auto-pilot (run end-to-end, pause only at decision/send gates) or review (confirm each step) mode. Stops before anything that sen

  • build-profile

    Build or update the JobClaw master profile — the single file every other job-hunt skill reads. Ingests a resume (extracting every embedded URL), LinkedIn PDF, exported AI-memory, and links, then asks only for what's missing in one batched, optional gap prompt. Captures career-goal context for downst

  • career-coach

    Coach-style multi-turn conversation grounded in the master profile. The ONE skill allowed to read AND paraphrase (never quote) the profile's `context:` block — career_goal and additional_info — to direct advice. Last 8 messages of history retained. Use when the user wants open-ended career advice —

  • coach-negotiation

    Coach a counter-offer — leverage analysis, floor / target / walk-away ranges per comp component, and a draft counter email the human sends (never auto-send). Reads companies/<slug>.json for market comp when present; otherwise asks for an inline range or runs a thin WebSearch. Region pack drives curr

  • draft-reply

    Draft a reply email matched to one of the taxonomy's reply intents — reply-schedule, reply-accept (with sub-templates for scheduling / assessment / offer), reply-decline, reply-ask, reply-info, follow-up. Mirrors inbound tone; interpolates dates / links; uses the profile's signature. Never auto-send

  • find-jobs

    Find relevant job listings for the user by combining multiple sources — Claude web search, ATS-direct boards (Greenhouse/Lever/Ashby/Workday/SmartRecruiters), Hacker News hiring, and optional APIs (Adzuna, SerpApi) with a Firecrawl scrape fallback — then normalize, dedupe across runs, and rank again

  • infer-status

    Resolve the canonical application status from signals (triage class + current status + days-since-apply / days-since-last-contact + optional portal state) using the taxonomy decision table. Emits {status, next_action, next_action_due_on, rationale}; optionally updates a flat tracker.json. Honours th

  • map-career-path

    Map a transition from a current role to a target role — surface real LinkedIn-style transition examples + a personalized gap roadmap (skills, experiences, signals) grounded in the user's profile. Optional Google CSE script (better recall) when keys are present; WebSearch fallback ships keyless. Use

  • mock-interview

    Run a text-based mock interview — one question at a time, capture the user's verbatim answer, end with a scored report per the shared report-schema. Defaults to 5 questions (matches Go original); configurable up to 10. Unanswered questions score 0. Forked. Use to practice for an upcoming round — ide

  • prep-interview

    Build an interview prep brief — 8–12 likely questions split across the loop's rounds, profile-grounded STAR talking points per question, a prep checklist, and diplomatic questions to ask back. Reads companies/<slug>.json from research-company if present; otherwise runs a thin in-line sweep. Forked c

  • render-resume

    Render a resume to a polished PDF via rendercv (Typst engine). Exposes all 9 built-in themes (engineeringresumes is the ATS-safe default) and embeds every link as a real, clickable PDF annotation. Reads the tailor-resume sidecar so the tailored content and links survive intact. Use after tailor-resu

  • request-human-input

    Decide whether a blocking situation needs human input; compose a mobile-first prompt with ≤ 3 quick-reply options + a stated timeout default; parse a free-text reply back into a structured decision. v0 reasoning-only — delivery (Telegram / WhatsApp) lives in JobClaw's HITL MCP, not here. Always pers

  • research-company

    Build a structured company × role brief — compensation, day-to-day, career growth, recent news, community sentiment (Reddit / Blind / Glassdoor), red flags, and a "fit for this user" view. Heavy reasoning — runs forked. Writes companies/<slug>.{md,json} sidecars consumed by prep-interview and coach-

  • review-render

    Visually QA a rendered resume PDF and auto-fix layout/content defects in a bounded loop: render → screenshot → deterministic gate → vision rubric → apply one fix → re-render, until it passes or hits a pass cap. Catches widows, under-fill, overflow, orphaned headers, and imbalance that text-only logi

  • score-fit

    Score how well the user's master profile fits a specific job — an ATS-style match percentage with matched/missing keywords, strengths, gaps, and a clear apply-or-skip recommendation. Optionally writes a structured sidecar that tailor-resume consumes. Use to evaluate a single job (or a few) against t

  • tailor-resume

    Produce a job-specific, ATS-optimized resume from the user's master profile and a target job — reordering, reframing, and surfacing the most relevant real experience and keywords. Enforces a content rubric (bullet shape, length, parallel grammar, metric coverage), then renders a polished PDF by defa

  • triage-inbox

    Classify a recruiting email (or a batch) into one of the 10 canonical email classes, extract structured fields (company / role / dates / links / asks / deadline / sentiment), and suggest the next action. Writes inbox/triage-<YYYY-MM-DD>.json — consumed by infer-status and draft-reply. Use when the u

  • write-cover-letter

    Produce a job-specific, profile-grounded cover letter in markdown — ≤ 350 words, ≤ 1 page, three paragraphs (hook → two quantified proofs → fit close). Reuses keywords from a prior tailor-resume sidecar when present. Writes a JSON sidecar reserved for a future /render-resume --kind cover-letter (ren

  • write-outreach

    Write a short, profile-grounded cold outreach message to a recruiter, hiring manager, or potential referrer — LinkedIn DM or email — with one clear CTA and no flattery. Use when the user wants to reach out cold for a referral, info chat, recruiter intro, or post-event/post-interview follow-up — targ

View source on GitHub

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