recsys-pipeline-architect
Design composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework popularized by xAI's open-sourced For You algorithm. Use this skill whenever the user is building any system that picks "the top K items for a (user, context)" — social feeds, content CMSs, RAG rerankers, task prioritizers, notification triage, search reranking, ad ranking.
npx skills add mturac/everything-openai-codex --skill recsys-pipeline-architect --agent codex
Same command for any agent — swap --agent for claude-code, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# recsys-pipeline-architect A spec-and-scaffold skill for building composable recommendation, ranking, and feed pipelines. It encodes the **six-stage pattern** — Source → Hydrator → Filter → Scorer → Selector → SideEffect — popularized by xAI's open-sourced [For You algorithm](https://github.com/xai-org/x-algorithm) (Apache 2.0). This skill is an independent reimplementation of the pattern (MIT) — no code copied from the original. Upstream: <https://github.com/mturac/recsys-pipeline-architect> ## When to Use - User wants to build any system that picks "the top K items for a user/context" - User asks "how should I rank X" or describes a feed/personalization problem - User has a scoring function and needs the pipeline plumbing around it - User wants to migrate from a single relevance score to multi-action prediction with tunable weights - User is wrapping an LLM/ML scorer and needs filters, hydrators, side-effects, and a runnable scaffold in their stack (TypeScript / Go / Python) - Triggers: "recommendation system", "feed algorithm", "ranking pipeline", "for you feed", "candidate pipeline", "content recommender", "pipeline architecture for recsys", "RAG retrieval reranker" ## When NO
- When to Use
- When NOT to Use
- The six-stage framework
- Why this exact order
- Workflow when invoked
- Key trade-offs to surface (don't default silently)
- 1. Single score vs multi-action prediction
- 2. Candidate isolation in scoring
- 3. Online vs offline
- Hard rules
- Anti-Patterns
- Upstream contents
What does the recsys-pipeline-architect skill do?
Design composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework popularized by xAI's open-sourced For You algorithm. Use this skill whenever the user is building any system that picks "the top K items for a (user, context)" — social feeds, content CMSs, RAG rerankers, task prioritizers, notification triage, search reranking, ad ranking.
How do I install it?
Run `npx skills add mturac/everything-openai-codex --skill recsys-pipeline-architect --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 mturac/everything-openai-codex, a repository with 84 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.