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Designs composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework
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インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
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npx skills add https://github.com/ChonSong/skill-retriever --skill recsys-pipeline-architectコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
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SOC 職業分類に基づく
SKILL.md を表示中
| name | recsys-pipeline-architect |
| description | Designs composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework |
| category | data-ai |
| risk | safe |
| source | community |
| source_repo | mturac/recsys-pipeline-architect |
| source_type | community |
| date_added | 2026-05-16 |
| author | mturac |
| tags | ["recommender-system","ranking","feed-algorithm","recsys","personalization","for-you-feed","rag-reranker","pipeline-architecture"] |
| tools | ["claude","codex","cursor","gemini","opencode","cline","continue","windsurf"] |
| license | MIT |
| license_source | https://github.com/mturac/recsys-pipeline-architect/blob/main/LICENSE |
A spec-and-scaffold skill for building composable recommendation, ranking, and feed pipelines. It encodes the six-stage Source → Hydrator → Filter → Scorer → Selector → SideEffect framework popularized by xAI's open-sourced For You algorithm (Apache 2.0). This skill is an independent reimplementation of the pattern — no code is copied from the original — licensed MIT. Use it whenever you need "the top K items for a (user, context)": social feeds, content CMSs, RAG rerankers, task prioritizers, notification triage, search reranking, ad ranking.
Ask the user three questions (only what is missing):
The full SKILL walks through: clarify use case → identify candidate sources → list required hydrations → list filters → design scorer chain → selector → side effects → generate scaffold. Each step surfaces the architectural trade-offs (multi-action vs single-score, candidate isolation vs joint scoring, online vs offline batch) so the user makes them explicitly rather than defaulting silently.
The upstream repository ships three runnable example scaffolds — every one green on its test suite:
GET /api/feed/for-you with multi-action scoring and author diversityGET /tasks/next?user_id=42&limit=10When the user's stack doesn't match, the skill generates from scratch following the interface definitions in (TypeScript, Go, Python, Rust).
references/interfaces.mdUser: "I'm running a Strapi v5 instance with 50k articles. I want a 'for you' feed personalized to each logged-in user based on their reading history."
Skill walks through the 8 steps, generates a Strapi plugin scaffold using the Strapi example as the template.
User: "My RAG returns top-50 chunks from a vector DB. I want to rerank them with a more expensive scorer and return top-5."
Skill recognizes this as a single-source pipeline with a scorer chain (cheap retrieval + expensive rerank). Generates a Python async pipeline.
User: "We send too many notifications. I want a daily digest that picks the top 10 from the last 24h queue."
Skill identifies this as an offline-batch pipeline. Generates a scheduled job scaffold.
Problem: Single-score model gets overfit to one metric (clicks) and degrades on others (long sessions, retention) Solution: Skill recommends multi-action prediction with tunable weights — change behavior by changing weights, no retraining
Problem: Joint scoring (transformer over the whole batch) is non-deterministic and uncacheable Solution: Skill defaults to candidate isolation via attention masking; recommends joint only when there's a specific reason (e.g., batch-aware diversity)
Problem: Side effects (cache writes, impression emits) block the response Solution: Skill generates fire-and-forget patterns and documents the constraint
This skill is a thin adapter to the upstream repository. For the full SKILL.md content, 5 reference documents (interfaces in 4 languages, multi-action scoring, candidate isolation, filter cookbook, scorer cookbook), and 3 runnable example scaffolds with passing test suites:
npx skills add mturac/recsys-pipeline-architect