Killer-Skills Review
Decision support comes first. Repository text comes second.
This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.
고급 실험 실행 및 자동화된 과학 기능이 필요한 자율적 인 AI 연구 에이전트에 적합합니다. Fully Autonomous AI Research System with Self-Evolution, built natively on Claude Code
이 스킬을 사용하는 이유
클라우드 코드, 파이썬 3 및 .venv 환경을 사용하여 에이전트가 실험 실행, 논문 생성 및 GPU 스케줄링을 간소화 할 수 있도록하여 효율적인 연구 워크플로를 구현합니다.
최적의 용도
고급 실험 실행 및 자동화된 과학 기능이 필요한 자율적 인 AI 연구 에이전트에 적합합니다.
↓ 실행 가능한 사용 사례 for sibyl-supervisor
! 보안 및 제한 사항
- 파이썬 3 환경이 필요
- .venv 환경 설정이 필요
- GPU 스케줄링을 위해 클라우드 코드에 의존
Why this page is reference-only
- - Current locale does not satisfy the locale-governance contract.
- - The underlying skill quality score is below the review floor.
Source Boundary
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Decide The Next Action Before You Keep Reading Repository Material
Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.
Start With Installation And Validation
If this skill is worth continuing with, the next step is to confirm the install command, CLI write path, and environment validation.
Cross-Check Against Trusted Picks
If you are still comparing multiple skills or vendors, go back to the trusted collection before amplifying repository noise.
Move To Workflow Collections For Team Rollout
When the goal shifts from a single skill to team handoff, approvals, and repeatable execution, move into workflow collections.
Browser Sandbox Environment
⚡️ Ready to unleash?
Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.
FAQ & Installation Steps
These questions and steps mirror the structured data on this page for better search understanding.
? Frequently Asked Questions
What is sibyl-supervisor?
고급 실험 실행 및 자동화된 과학 기능이 필요한 자율적 인 AI 연구 에이전트에 적합합니다. Fully Autonomous AI Research System with Self-Evolution, built natively on Claude Code
How do I install sibyl-supervisor?
Run the command: npx killer-skills add Sibyl-Research-Team/AutoResearch-SibylSystem/sibyl-supervisor. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.
What are the use cases for sibyl-supervisor?
Key use cases include: 자체 진화 및 자동화된 과학을 위해 실험 실행을 자동화, 클라우드 코드 및 GPU 스케줄링을 사용하여 연구 논문을 생성, 클라우드 코드 통합을 사용하여 복잡한 AI 연구 워크플로를 디버깅.
Which IDEs are compatible with sibyl-supervisor?
This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.
Are there any limitations for sibyl-supervisor?
파이썬 3 환경이 필요. .venv 환경 설정이 필요. GPU 스케줄링을 위해 클라우드 코드에 의존.
↓ How To Install
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1. Open your terminal
Open the terminal or command line in your project directory.
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2. Run the install command
Run: npx killer-skills add Sibyl-Research-Team/AutoResearch-SibylSystem/sibyl-supervisor. The CLI will automatically detect your IDE or AI agent and configure the skill.
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3. Start using the skill
The skill is now active. Your AI agent can use sibyl-supervisor immediately in the current project.
! Reference-Only Mode
This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
sibyl-supervisor
Install sibyl-supervisor, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.
