Directorio de skills

Descubre skills reutilizables para AI agents.

Busca skills reales de GitHub por tarea y revisa stars, confianza, auditoría, categoría y ruta de instalación antes de utilizarlos.

Cada recomendación conserva un vínculo claro con su repositorio, auditoría y ruta de instalación.

Resultados de búsqueda: kd-tree

Directorio en inglés

Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption

14K
Stars
80/100
Confianza
Categoría: agent-frameworksAuditoría

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.

18K
Stars
87/100
Confianza
Categoría: ml-automationAuditoría
Sem84

Semantic version control => entity-level diffs, blame, and impact analysis on top of git. 26 languages via tree-sitter. Built for coding agents.

3.2K
Stars
84/100
Confianza
Categoría: agent-frameworksAuditoría

Crabbox: warm a box, sync the diff, run the suite.

1.3K
Stars
81/100
Confianza
Categoría: utilityAuditoría

6,100+ brand SVG icons for developers. Tree-shakeable, typed, open source. npm i thesvg

2.4K
Stars
84/100
Confianza
Categoría: agent-skillsAuditoría
Evo84

turns your codebase into an autoresearch loop — discovers what to measure, instruments the benchmark, then runs tree search with parallel subagents.

1.2K
Stars
84/100
Confianza
Categoría: agent-skillsAuditoría

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.

161
Stars
76/100
Confianza
Categoría: coding-agentsAuditoría

A lightweight configuration/utility that prevents coding agents like Codex and Claude Code from over-engineering tasks with unnecessary modules, subagents, dependencies, and hashes.

141
Stars
77/100
Confianza
Categoría: coding-agentsAuditoría

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`.

51K
Stars
79/100
Confianza
Categoría: researchAuditoría

Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.

34K
Stars
77/100
Confianza
Categoría: data-analysisAuditoría

A python library for decision tree visualization and model interpretation.

3.1K
Stars
75/100
Confianza
Categoría: ml-automationAuditoría

How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.

34K
Stars
78/100
Confianza
Categoría: design-creativeAuditoría