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GigWatch is an open-source, self-hosted software project that polls job and gig feeds on a schedule, filters the listings against your skills and other rules, remembers what it has already shown you, and alerts you only when something new matches. It is a program you run yourself, not a website you visit, and it does not need dedicated hardware: the project’s documentation describes running it on a laptop, from cron, in Docker, or on a VPS.
The problem it targets is familiar to anyone who job-hunts across several boards. You open each site in turn, scan for anything new, and try to remember whether you already saw a listing last week. GigWatch replaces that routine with a repeated, automated check and a seen-list that does the remembering.
What GigWatch does in one pass
Each run of GigWatch fetches listings from the sources you configure, applies your filters, compares the results against a local state file that records listings it has already processed, and sends alerts for new matches. According to the project README on GitHub (earnnova-dev/gigwatch), the state file is what deduplicates results between runs, so a listing you have already been notified about does not trigger a second alert on the next scan.
The README documents three alert channels: console output, email, and Slack. Filters can be set by category, location, and exclusion terms, and the project includes a relevance score that gives hits in a listing’s title more weight than hits in its body text. That weighting matters in practice: a posting titled with your core skill will outrank one that mentions it only in passing deep in the description.
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The commands and what each one is for
The project exposes four commands. The table below uses the names and descriptions given in the README; check the README for the exact invocation syntax in the version you install.
| Command | What it does, per the README | When it fits |
|---|---|---|
watch |
Repeats scans of your sources and alerts on new matches | You want near-immediate notice of new listings |
digest |
Batches matches for delivery instead of sending each one as it appears | You prefer one summary a day over a stream of alerts |
serve |
Runs a dashboard, a JSON endpoint, an RSS endpoint, and a health probe | You want to browse results in a browser, feed them into another tool, or monitor the process |
rank |
Scores listings against a profile and explains the result | You want to see why a listing scored the way it did, not just whether a keyword matched |
Where the listings come from
GigWatch does not scrape arbitrary sites. It reads from feeds and endpoints, and the README separates two kinds of coverage.
Built-in sources
The README lists five built-in sources: Remotive, We Work Remotely, RemoteOK, Jobicy, and Hacker News “Who is Hiring?”. These are the boards the project ships with a dedicated connector. The article that introduced the project does not enumerate its five boards, so the five named here come from the repository, not the article.
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Generic RSS, Atom, and JSON feeds
Any board or aggregator that publishes an RSS or Atom feed, or a JSON endpoint, can be added as a source without a dedicated connector. This is the path to use for a board that is not on the built-in list, provided that board actually publishes a usable feed.
LinkedIn and Upwork
Neither is a built-in connector. The README describes LinkedIn through RSS-based access, and it lists Upwork on its roadmap as an import from a user-supplied export. If you want either site covered, plan on that route rather than expecting a ready-made integration.
Filtering and ranking: two different jobs
Filtering answers a yes-or-no question: does this listing pass my category, location, and exclusion rules? Ranking answers how well a listing fits a profile. GigWatch keeps these separate, which lets you use strict filters to cut noise and a ranking pass to order what remains.
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The README says ranking can use an LLM when an API key is configured and falls back to a deterministic heuristic otherwise. The two modes behave differently, and the README does not compare their accuracy or cost.
| Ranking mode | Condition | Behaviour stated in the README | Accuracy and cost comparison |
|---|---|---|---|
| LLM-based | An API key for a language-model endpoint is configured | Uses the model to score listings against the profile | Not stated |
| Deterministic heuristic | No API key is configured | Scores listings with fixed rules, so the same input gives the same score | Not stated |
In practice, the heuristic mode is the one you can run with no external account. If you use the LLM mode, the listing text and your profile are sent to whichever endpoint you configure, so review that endpoint’s data handling before enabling it.
Installing and running it
The README gives two installation routes: from source, or with pip or pipx. The project describes itself as standard-library-only, so there is no large dependency tree to manage beyond the Python runtime. Following the README, the usual setup is to configure your sources, filters, and alert channels, run a scan to confirm output, and then schedule it.
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Choosing where it runs
The README documents four deployment patterns. Each suits a different level of uptime and maintenance.
- Laptop: simplest to start, but scans only happen while the machine is awake and running the process.
- Cron: schedules repeated runs on a machine that stays on, without keeping a process open.
- Docker: packages the setup in a container so it can move between machines more predictably.
- VPS: keeps scanning when your own computer is off. It is an option, not a requirement.
The README does not establish how these setups compare for security or reliability. If you expose the serve dashboard or its endpoints beyond your own machine, add your own access controls, because the project documentation does not settle that question for you.
How to read the example numbers
A DEV Community article published on September 29, 2026 reports two figures from the author’s own runs. Both are examples, not measurements the project makes about itself.
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- In a dry-run example, the tool fetched 362 jobs and 22 matched the author’s filters.
- In a displayed sample, one source returned 17 jobs; four matched the filter and two were new since the previous run.
These numbers show the funnel from fetched listings to matches. They do not tell you how many listings a board will carry on a given day, how often your own filters will match, or how the tool performs across feeds. Run it against your own sources and filters to get a figure that means something for you.
Hosted option and pricing
The README also documents an optional hosted tier at $29 per month and a one-time custom-setup option at $99. Those are the prices stated in the repository as of the time it was accessed in 2026. The core software is free, so these are paid convenience services layered on top of it, not a requirement to use GigWatch. Current availability and purchase terms were not verified, so check with the maintainer before budgeting for either.
Who should use it
GigWatch suits a particular kind of job seeker, and it is a poor fit for others. Use this checklist to decide:
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- You already check the same handful of boards on a regular basis and want that check automated.
- Your target boards are among the five built in, or they publish RSS, Atom, or JSON feeds.
- You are comfortable installing a Python tool, editing a configuration file, and scheduling a job with cron or Docker.
- You want to keep your data local and avoid a third-party job-alert service.
It is less suitable if your main sources are sites that offer no feed and no export, if you need a managed service with guaranteed uptime, or if you want a point-and-click experience with no configuration. Before you add any board, read that site’s terms of use: the README does not establish the feed terms of the boards it reads, so that check is yours to make.
Quick Recap
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