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name: x-architecture description: Use this skill when reasoning about the distributed system design, service orchestration, or request lifecycle of the X recommendation engine. It is essential for tasks involving the "For You" timeline construction, HomeMixer logic, or ProductMixer component definitions. version: 1.0.0 license: MIT

X Algorithm Architecture

Master reference for the X (Twitter) recommendation engine architecture, specifically the HomeMixer orchestration layer, ProductMixer functional components, and the Scala-to-Rust candidate pipeline bridge.

Context

The X recommendation engine operates as a "Lambda Architecture" variant. The orchestration layer (HomeMixer) is written in Scala using the ProductMixer framework, which defines the business logic graph. High-compute tasks (Candidate Retrieval, Scoring) are offloaded to optimized services (Rust/C++/Java).

For detailed technical breakdowns, see:

• Pipeline Lifecycle
• Service Map

What it does

• Maps the Request Graph: Traces the execution path from HomeMixer down to leaf services like Earlybird (Search) and Navi (ML Scoring).
• Defines ProductMixer Traits: Explains the specific Scala traits used to build feed features: CandidateSource, Filter, Scorer, Gate, Selector, and SideEffect.
• Identifies Data Models: Recognizes key data structures like SimClusters (Community Embeddings), TwHIN (Knowledge Graph), and RealGraph (User Interaction probabilities).
• Locates Logic: Helps determine if logic resides in the orchestration layer (Scala) or the compute layer (Rust/Thrift).

Guidelines

• Directory Navigation:
  • home-mixer/: Main orchestration logic for the timeline.
  • product-mixer/: Core framework defining how pipelines are built.
  • cr-mixer/: Content Recommender Mixer (Out-of-Network retrieval logic).
  • navi/: ML Model serving infrastructure (Heavy Ranker host).
  • visibility-lib/: Rust-based filtering logic (Safety, Blocks, Mutes).
• ProductMixer Hierarchy: The system is composed of pipelines.
  1. Mixer Pipeline: The top-level entry (e.g., "For You").
  2. Candidate Pipeline: Parallel fetching of candidates (e.g., "In-Network", "Ads", "Who to Follow").
  3. Functional Components: Atomic units of logic (Filter, Scorer, Hydrator).
• Scoring Stages: distinguish between Light Ranking (fast, heuristic-based, often inside Earlybird) and Heavy Ranking (full neural network, hosted in Navi).
• Candidate Isolation: In the Heavy Ranker (MaskNet/Transformer), candidates are scored in a batch but cannot attend to each other (no cross-candidate attention). They only attend to the User Context.
• Thrift Boundaries: Scala components communicate with Rust services via Thrift. If a field isn't in the Thrift definition, HomeMixer cannot see it.
• Feature Stores: Understand that SignalIngester and UserSignalService provide the raw interaction data that feeds SimClusters and RealGraph.

Example Trigger Prompts

• "/trace-feed ForYou"
• "/trace-feed HomeMixer → HeavyRanker"
• "/trace-feed CandidateSource vs Gate in ProductMixer"
• "Where are SimClusters embeddings injected in the pipeline?"
• "Explain cr-mixer’s Out-of-Network candidate generation"
• "How does visibility-lib enforce feed filtering?"