recsys-topic-selection
Use when deciding whether a project is a strong ACM RecSys fit, routing among RecSys, SIGIR, KDD, WSDM, TheWebConf, UAI, CHI, and general ML venues, identifying whether the core contribution is genuinely about recommendation, and choosing the right RecSys track before writing begins.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill recsys-topic-selection --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# RecSys Topic Selection Use this before writing. RecSys is a **single-domain** venue: it is strongest when the central claim is about **recommendation** — ranking objectives, user/item modeling, offline/online evaluation, feedback loops, exposure and fairness, or deployed recommender behavior. Being merely *applicable* to recommendation is not enough; the contribution has to speak to a recommende
What does the recsys-topic-selection skill do?
Use when deciding whether a project is a strong ACM RecSys fit, routing among RecSys, SIGIR, KDD, WSDM, TheWebConf, UAI, CHI, and general ML venues, identifying whether the core contribution is genuinely about recommendation, and choosing the right RecSys track before writing begins.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill recsys-topic-selection --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.