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: delete

Directorio en inglés

Reviews animation and motion code against a high craft bar derived from Emil Kowalski's design engineering philosophy. Default to flagging; approval is earned.

18K
Stars
87/100
Confianza
Categoría: design-creativeAuditoría

Vendor-agnostic orchestration for training, inference and agentic workloads across NVIDIA, AMD, TPU, and Tenstorrent on clouds, Kubernetes, and bare metal.

2.2K
Stars
85/100
Confianza
Categoría: agent-skillsAuditoría

Entity Framework EF Core efcore Bulk Batch Extensions with BulkCopy in .Net for Insert Update Delete Read (CRUD), Truncate and SaveChanges operations on SQL Server, PostgreSQL, MySQL, SQLite, Oracle

4.0K
Stars
73/100
Confianza
Categoría: data-analysisAuditoría

A powerful browser extension to create, edit and delete cookies

1.6K
Stars
75/100
Confianza
Categoría: legal-complianceAuditoría

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

51K
Stars
83/100
Confianza
Categoría: researchAuditoría

Agent skills for Fallow codebase intelligence tool that helps AI agents detect unused code, duplication, circular dependencies, complexity hotspots, and architecture drift in JavaScript and TypeScript projects.

114
Stars
73/100
Confianza
Categoría: developmentAuditoría

Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.

34K
Stars
70/100
Confianza
Categoría: researchAuditoría

Use when the user wants to run the cognee API server (and optional UI) on their own machine — starting it, checking it's healthy, connecting the SDK or other clients to it, and choosing the right auth posture.

30K
Stars
75/100
Confianza
Categoría: design-creativeAuditoría

Use when the user needs something that ships outside cognee core — community database adapters (Qdrant, Milvus, Weaviate, Redis, Pinecone, FalkorDB, Memgraph, DuckDB, NetworkX, …), data-source connectors (Slack, Gmail, Notion, Confluence, Google Drive), custom tasks/pipelines/retrievers (Exa, ScrapeGraph, codify), Keywords AI observability — or wants to contribute a package to the cognee-community repo.

30K
Stars
74/100
Confianza
Categoría: researchAuditoría

Use when the user wants to drive cognee from the terminal with cognee-cli — remember/recall/forget/improve memory commands, managing datasets and config, or database migrations.

30K
Stars
68/100
Confianza
Categoría: data-analysisAuditoría

Use when working with cognee's permission system — understanding or changing how users, roles, and tenants get access to datasets, how ACL grants work, where permissions are enforced in add/cognify/search/delete, and how the grant records surface in the memory-provenance view.

30K
Stars
73/100
Confianza
Categoría: researchAuditoría