Direktori skill

Temukan skill yang dapat digunakan kembali untuk AI agents.

Cari skill GitHub nyata berdasarkan tugas lalu periksa stars, trust, audit, kategori, dan jalur pemasangan sebelum digunakan.

Setiap rekomendasi tetap terhubung dengan repositori, audit, dan jalur pemasangannya.

Hasil pencarian: debate

Direktori bahasa Inggris

AI coding dream team of agents for VS Code. Claude Code + openai Codex collaborate in brainstorm mode, debate solutions, and synthesize the best approach for your code.

1.1K
Stars
84/100
Kepercayaan
Kategori: agent-frameworksAudit

Agentic, long-horizon visual generation: a fuzzy story → a cross-model-audited image-based movie. Brings ARIS's research-wiki + multi-agent debate to multimodal generation (intelligence lives in the agent; the diffusion model just renders). Image-based today, video next.

46
Stars
69/100
Kepercayaan
Kategori: utilityAudit

A multi-agent newsroom that transforms documents into a cross-linked wiki using local LLMs, designed for agent runtimes like Claude Code.

77
Stars
67/100
Kepercayaan
Kategori: researchAudit

A Claude Code plugin that orchestrates 4-6 AI reviewers to debate and judge code, plans, or docs with structured multi-stance review and domain checklists.

30
Stars
69/100
Kepercayaan
Kategori: coding-agentsAudit

Plugin de skills e agentes para Claude Code workflows de engenharia reais, do PRD ao PR

19
Stars
63/100
Kepercayaan
Kategori: utilityAudit

Nine quality-canary skills for AI coding agents covering code health, rule completeness, grounding, supply chain, resilience, and drift, with auto-cadence hooks for session start/end.

11
Stars
63/100
Kepercayaan
Kategori: coding-agentsAudit

Curated collection of AI agent skills for Hermes and other agent frameworks

11
Stars
63/100
Kepercayaan
Kategori: utilityAudit

A CLI and skill harness that adds real-world capabilities like image, video, web search to coding agents such as Claude Code, Cursor, and Codex.

39
Stars
64/100
Kepercayaan
Kategori: coding-agentsAudit

A reusable agent decision workflow that forces AI agents to debate financial trades and settles via code, installable across multiple agent runtimes.

10
Stars
68/100
Kepercayaan
Kategori: finance-quantAudit

Use when building AI agents with agentfootprint — LLMCall, Agent, skills, RAG, memory, control flow, Swarm concepts, mock/anthropic/openai/ollama providers, tools, recorders, resilience, and streaming. Also use when someone asks how agentfootprint works or wants to understand the framework.

20
Stars
61/100
Kepercayaan
Kategori: design-creativeAudit