React and Next.js performance guidance for writing, reviewing, and refactoring production UI code.
Directorio de skills
Descubre skills reutilizables para AI agents.
Cada recomendación conserva un vínculo claro con su repositorio, auditoría y ruta de instalación.
Resultados de búsqueda: expression-tree
Directorio en inglésSelf-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Semantic version control => entity-level diffs, blame, and impact analysis on top of git. 26 languages via tree-sitter. Built for coding agents.
Crabbox: warm a box, sync the diff, run the suite.
6,100+ brand SVG icons for developers. Tree-shakeable, typed, open source. npm i thesvg
turns your codebase into an autoresearch loop — discovers what to measure, instruments the benchmark, then runs tree search with parallel subagents.
AI Agent Skill for Prompting Video Models
A Claude Code plugin that provides a universal radial-tree exploration engine with swappable presets for divergent ideation, adversarial critique, design-space exploration, and code audit.
A lightweight configuration/utility that prevents coding agents like Codex and Claude Code from over-engineering tasks with unnecessary modules, subagents, dependencies, and hashes.
Glisp is a Lisp-based design tool that combines generative approaches with traditional design methods, empowering artists to discover new forms of expression.
Automated Cherry Studio review for local branches, PRs, commits, files, architecture docs, and repository skills. Use for code or documentation reviews that need project-specific naming, main/renderer/shared placement and dependency rules, IpcApi and DataApi boundaries, lifecycle/service ownership, renderer hooks, React/UI conventions, and tests. Supports single-agent review with interactive fix selection or multi-agent reviewer-verifier review with risk-based auto-fix. To diagnose gaps in the skill after a review session, run `/gh-pr-review diag`.