jobfitlisted

Job-fit evaluation and discovery for job seekers — "find roles that fit me" and "should I apply to this one?" DISCOVER searches job boards for openings matching your profile; EVALUATE takes job URLs/descriptions you provide. Both research compensation, company signal, and posting legitimacy in parallel, score each role A–F, and emit a ranked decision brief with tailored CV-bullet suggestions. Evaluated roles persist in out/jobfit/tracker.md so repeat runs skip what you passed on. Keyless and human-in-the-loop: it never applies for you. Use to find matching jobs, triage postings, decide whether a role is worth applying to, or tailor a CV to a JD — e.g. "find jobs that fit my CV", "/jobfit <url>", "score these roles against my CV". For community buzz on a company use pulse.
duthaho/skillhub · ★ 6 · AI & Automation · score 75

Install: claude install-skill duthaho/skillhub

# jobfit — job-fit evaluation & tailoring `/jobfit [url(s) | pasted JD(s)] [profile path/URL or plain-language steering]` Answer one question per role: **is this worth applying to, and if so, how do I tailor for it?** You ground every judgment in the actual posting + light research, score against the user's real profile, and rank by fit. ## Two modes (auto-detect) - **EVALUATE** — the user provides one or more job URLs/JDs. Score and tailor those. - **DISCOVER** — the user provides **no** jobs (e.g. "find jobs that fit my CV"). Source matching openings from the profile, let the user pick, then evaluate those. If jobs are given → EVALUATE. If none are given → DISCOVER. If the user gives jobs but also says "and find more like these," do both: evaluate the given ones and run Step 0b. ## Source-of-truth boundary (read first) User-facing content and scores draw **only** from: 1. the **actual job posting(s)** the user provides, points to, or that DISCOVER surfaces, 2. the user's **profile** (see Step 0), and 3. what the user states **in this session**. **Keywords get reformulated, never fabricated.** Never invent experience, skills, metrics, titles, or achievements the profile doesn't support. Never pull "facts" about the user from memory or cross-session inference. Using a tool is not building it — never claim authorship of systems the profile only shows the user used. Tailoring = surfacing and rephrasing what's genuinely there to mirror the JD's language. ## The track