Results for “sharing-model”

Ownership models are usually inherited rather than chosen, and the inherited one

Design, create, and manage Salesforce sharing rules to grant record access beyond the role hierarchy, covering owner-based, criteria-based, and guest user rules.

Stores shared reference documents and model mapping catalogs consumed by other SDD skills; not invokable as a skill itself.

Programmatically publish and monitor content distribution in AEM Cloud Service using the Replication API and Sling Distribution events.

Expert guidance for distributed NoSQL databases (Cassandra, DynamoDB). Focuses on mental models, query-first modeling, single-table design, and avoiding hot partitions in high-scale systems.

Skill for the _shared area of paddock. 33 symbols across 6 files.

Design scalable distributed systems using structured approaches for load balancing, caching, database scaling, and message queues.

Merge multiple fine-tuned models using mergekit to combine capabilities without retraining, covering SLERP, TIES-Merging, DARE, Task Arithmetic, linear merging, and production deployment strategies.

Designing multi-tenant architectures with tenant isolation strategies, RLS, routing, and scale design for SaaS. Use when designing multi-tenant SaaS systems or tenant isolation.

Engineer word-of-mouth and virality using the STEPPS framework (Social Currency, Triggers, Emotion, Public, Practical Value, Stories).

Engineer word-of-mouth and virality using the STEPPS framework (Social Currency, Triggers, Emotion, Public, Practical Value, Stories). Use when the user mentions "go viral", "word of mouth", "shareable content", "social currency", "why people share", "viral loop", "referral program", or "organic growth". Also trigger when designing shareable features, crafting social media campaigns, or building products that spread through peer recommendation. Covers environmental triggers and high-arousal emotional content. For sticky messaging, see made-to-stick. For persuasion tactics, see influence-psychology.

Guides users through participating in the SOMA decentralized training network, covering data submission, model training, reward claiming, and strategic optimization.

Expert guidance for distributed NoSQL databases (Cassandra, DynamoDB). Focuses on mental models, query-first modeling, single-table design, and avoiding hot partitions in high-scale systems.

Renders a story, question, or meme as a realistic Reddit post card with vote rail, comments, and awards, suitable for video overlays or social media sharing.

Deploy trained machine learning models as production-ready services using REST APIs, containers, serverless functions, and orchestration platforms. Use when the user requests model deployment or provides relevant inputs for this workflow.

TRAK: Attributing Model Behavior at Scale

Design habit-forming product loops using the Hook Model (Trigger, Action, Variable Reward, Investment). Use when the user mentions "users arent coming back", "engagement loops", "habit formation", "push notifications", "variable rewards", "daily active users", "habit zone", or "user retention loops". Also trigger when designing notification strategies, building streaks or progress systems, or analyzing why users stop using a product after initial signup. Covers ethics evaluation and onboarding for habits. For friction reduction and B=MAP, see improve-retention. For viral sharing, see contagious.

Build and sharpen a project's domain model. Use when the user wants to pin down domain terminology or a ubiquitous language, record an architectural decision, or when another skill needs to maintain the domain model.

Provides production-grade Django architecture patterns including project structure, model design, REST API design with DRF, ORM best practices, caching, signals, and middleware.

Provides Spring Boot architecture patterns for building scalable REST APIs, including layered services, data access, caching, async processing, and logging.

跨X、LinkedIn、Threads和Bluesky的多平台内容分发。使用内容引擎模式根据平台适配内容。从不跨平台发布相同内容。当用户希望跨社交平台分发内容时使用。

Model software around the business domain using bounded contexts, aggregates, and ubiquitous language. Use when the user mentions "domain modeling", "bounded context", "aggregate root", "ubiquitous language", "anti-corruption layer", "context mapping", "domain events", or "strategic design". Also trigger when splitting a monolith into services, defining microservice boundaries, or aligning code structure with business processes. Covers entities vs value objects, domain events, and context mapping strategies. For architecture layers, see clean-architecture. For complexity, see software-design-philosophy.

Use when provisioning multi-tenant infrastructure, setting up tenant isolation, managing tenant lifecycles, or handling tenant-specific resource allocation. This skill provides standardized patterns for multi-tenant SaaS operations.

Configure ViewModel state emission with StateFlow, SharedFlow, and sealed UiState classes in Android. Use for state modeling and sharing policies; defer generic lifecycle collection, navigation-event plumbing, Hilt injection, test code, and configuration-change recipes to their specific skills.

v5.6.0 joint multi-TF model: single model per symbol with broadcast 1Hour context replaces dual 15Min/1Hour models. Trigger: (1) replacing weighted-voting model aggregation, (2) adding broadcast features to vectorized env, (3) limited training data + worried about overfitting from doubling obs_dim, (4) backtest builder mismatch with newer feature counts.

Pick the attribution model that fits the question, then build it. First touch, last touch, or multi-touch, each with its blind spots named out loud, turned into an honest channel-contribution read. Built for B2B RevOps and marketing teams, customizable to your CRM and your channel taxonomy. Trigger on "build attribution", "which channels drive pipeline", "first vs last touch", "how should we credit marketing", "what's working in our funnel", or any attribution diagnostic.

Merge multiple fine-tuned models using mergekit to combine capabilities without retraining. Use when creating specialized models by blending domain-specific expertise (math + coding + chat), improving performance beyond single models, or experimenting rapidly with model variants. Covers SLERP, TIES-Merging, DARE, Task Arithmetic, linear merging, and production deployment strategies.

JS Mixin Pattern

Merge multiple fine-tuned models using mergekit to combine capabilities without retraining. Use when creating specialized models by blending domain-specific expertise (math + coding + chat), improving performance beyond single models, or experimenting rapidly with model variants. Covers SLERP, TIES-Merging, DARE, Task Arithmetic, linear merging, and production deployment strategies.

High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.

Expert guidance for distributed NoSQL databases (Cassandra, DynamoDB). Focuses on mental models, query-first modeling, single-table design, and avoiding hot partitions in high-scale systems.

Share state between Blazor components across render mode boundaries using cascading values, scoped services with change events, or CascadingValueSource via DI.

Build and scale partner ecosystems that drive revenue and platform adoption, covering program design, tiering, co-marketing, build-vs-partner decisions, and structured deployment.