Skill UI

A comprehensive reference architecture for building scalable, cost-effective, and robust AI services. This system manages the full AI lifecycle, including intelligent model routing (for quality/cost trade-offs), response caching (using Redis), asynchronous batch processing, and fine-tuning pipeline management via Together AI's OpenAI-compatible API. Ideal for enterprise applications requiring high availability across multiple open-source models.

This guide details the implementation of the EventHandler pattern for robust, event-driven architecture. Learn how to create handlers that react to the system's domain events (lifecycle hooks), process payloads, and publish custom domain events. Crucially, it enforces architectural best practices by ensuring handlers act as thin orchestrators, delegating all core business logic to separate, reusable service abstractions.

This skill serves as a compatibility test to ensure that skills compiled from MDA (Metadata Definition Architecture) sources are correctly recognized and installed by the OpenClaw platform. It validates the integrity of the skill loading process, confirming successful parsing and integration.

This skill guides users through an in-depth interview process to achieve maximum project context completeness (100% "Gold Code") for their .faf file. By systematically asking questions about project goals, architecture, and technology stack, it ensures all critical context slots are filled, making the project fully structured and highly readable by AI systems.

A comprehensive guide for training or fine-tuning advanced sentence-transformer models. This skill assists in selecting the correct architecture—including Bi-encoders (SentenceTransformer), CrossEncoders (for reranking), and SparseEncoders—for various Natural Language Processing (NLP) tasks. Use cases include semantic retrieval, similarity matching, document clustering, and pair-wise classification.

Create engaging and intuitive process visualization using the whiteboard aesthetic. This template simulates a physical brainstorming session with sticky notes, hand-drawn SVG connections, and optional cursor interactions, perfect for onboarding, system architecture, or operational workflows.

This skill reviews code changes against accepted Architecture Decision Records (ADRs) to detect violations, drift, and non-compliance. It helps ensure that code modifications respect the architectural decisions agreed upon by the team. Use it before merging PRs or during periodic compliance checks. The process involves analyzing diffs, searching for relevant ADRs, checking constraints, and generating a compliance report with suggestions for violations.

This model provides an engineering operational framework for teams that leverage AI agents to generate large volumes of code. It shifts the focus from simple syntax to process quality, robust architecture design, rigorous testing, and systematic risk control, ensuring the development of highly stable and reliable systems in AI-assisted environments.

A comprehensive guide to architectural patterns for building scalable, production-ready backend services using Java and Spring Boot. Covers essential topics including RESTful API design, layered architecture (Controller, Service, Repository), data persistence (JPA), caching, asynchronous processing, robust error handling, and middleware filtering.

A detailed model of the ACM/IEEE Design Automation Conference (DAC) research manuscript review process. This guide explains the double-blind, TPC-driven, and single-shot nature of the evaluation, emphasizing the critical balance between genuine novelty and measured Quality-of-Results (QoR). It outlines the high standards for evidence fairness, benchmark credibility, and ablation studies required for acceptance, differentiating DAC's approach from architecture and software venues.

A comprehensive guide on achieving scientific reproducibility for complex computer architecture and system simulations. It details how to manage and pin all dependencies—including simulator commit hashes, local patches, workload binaries, hardware states, and post-processing scripts—to ensure that every reported figure and number can be accurately regenerated, regardless of time or environment changes.

Provides an in-depth strategic guide to the academic conference submission pipeline, using ISCA as a detailed case study. It meticulously details the two-round review structure, the critical rebuttal/revision window, and offers actionable strategies for authors to navigate reviewer feedback, committee deliberations, and the final decision-making process in top-tier architecture venues.