JobRadar: Open-source job search agent that scores listings with a local LLM
JobRadar is an open-source command-line tool that aggregates job listings from eight free sources and ranks them using a local large language model. The AI component provides scores and notes on skill, experience, salary, and remote fit, but users retain final decision authority. The system operates entirely offline and includes a web dashboard for visual management.
- ▪JobRadar pulls job postings from Remotive, Arbeitnow, RemoteOK, Jobicy, Himalayas, Greenhouse, Ashby, and optionally LinkedIn.
- ▪It scores each listing 0-100 using a locally run LLM, supporting Ollama or llama.cpp backends.
- ▪The installer automatically checks for required dependencies, installs Python, pip packages, and the chosen LLM model.
- ▪A web dashboard at localhost:3000 offers a dark‑mode SPA with Kanban view, filters, and configuration editing.
Hacker News (AI / LLM) files mainly under ai. We currently carry 3,262 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/ANIRudH-lab-life/job-radar |
| Publication time | Sun, 02 Aug 2026 05:30:33 +0000 |
| Retrieval time | 2026-08-02T05:45:40.612Z |
| Last seen | 2026-08-02T05:45:40.612Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | aODbdqZ7lmSD · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
🎯 JobRadar A CLI job search agent that hunts across 8 free sources at once and helps you figure out which ones are actually worth your time. It uses a local LLM to score jobs against your profile — but the AI is just a guide, not a decision-maker. You're the one who decides what fits. That's the whole point. Why JobRadar? Most job boards show you hundreds of listings and leave you drowning in tabs. JobRadar pulls from multiple sources at once, filters out the noise, and gives you a ranked list with AI-generated notes on why each job might (or might not) be a fit. But here's the thing: we believe the best job search tool puts a human in the loop.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.