picoruby-development-constraints
Documents memory limits and stdlib constraints for PicoRuby on ESP32. Use this when writing code that will run on ESP32 hardware or designing features for PicoRuby applications.
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Documents memory limits and stdlib constraints for PicoRuby on ESP32. Use this when writing code that will run on ESP32 hardware or designing features for PicoRuby applications.
Defines coding standards, test patterns, and language conventions for this project. Use this when writing code, comments, documentation, or git commit messages.
Guides developers through scenario test debugging using Ruby debug gem step execution. Provides interactive debugging patterns and test helper context.
Provides guidelines for maintaining and updating documentation alongside code changes. Use this when implementing features, fixing bugs, or changing APIs that affect user-facing documentation.
Guides AI agents through TDD workflow, build system safety, git operations, and TODO management for gem development. Use this when starting development sessions, managing tasks, or needing workflow clarificatio...
Leverage iterator chains for efficient, lazy data processing without intermediate allocations. Use when processing collections.
Build mithril-core shared infrastructure. Use when implementing storage, compression, hashing, or common types for the Mithril ML toolkit.
Instrument code with tracing spans and structured logging. Use for observability and performance analysis.
Implement GPU scheduling with VRAM budgets, work queues, and model lifecycle management. Use when building ML pipeline orchestrators.
Minimize allocations and cloning using references, Cow, and smart pointers. Use when optimizing hot paths or memory-constrained code.
Build mithril-checkpoint compression for PyTorch models. Use when implementing byte grouping, compression pipeline, or checkpoint I/O.
Run security scans locally (Semgrep, Trivy, Gitleaks) to detect vulnerabilities, secrets, and code issues before pushing. Use when the user wants to check for security issues, scan dependencies, or validate cod...
Initialize Rust projects with proper structure, essential crates, and Cargo.toml configuration. Use when starting new Rust binaries or libraries.
Manage Git worktrees for parallel feature development. Use when the user wants to work on multiple branches simultaneously, create worktrees, switch between features, open terminals/editors for worktrees, or ma...
Write async tests with tokio::test and configure multi-threaded test runtimes. Use when testing async code.
Manage concurrent operations with channels, semaphores, locks, and streams. Use when coordinating parallel work or limiting resource usage.
Build native Rust ML models with Candle framework. Use when implementing vision transformers, LLMs, or audio models with GPU acceleration.
Build mithril-dedup for ML dataset deduplication. Use when implementing MinHash, LSH, clustering, or document I/O.
Implement native Rust ML inference with Candle framework. Use when building GPU-accelerated ML pipelines without Python dependencies.
Structure Rust code using modules, traits, builders, and newtypes. Use when designing APIs, abstracting behavior, or preventing type confusion.
Build mithril-cache for torch.compile caching. Use when implementing content-addressable storage, cache keys, eviction, or framework hooks.
Create mocks using mockall and trait-based abstractions. Use when unit testing code with external dependencies.
Port HuggingFace models to Candle with correct tensor naming. Use when debugging weight loading errors or matmul issues.
Create new Claude Code skills with proper structure and conventions. Use when the user wants to create a new skill, scaffold skill templates, or understand skill anatomy.
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.