Skip to main content
Manus에서 모든 스킬 실행
원클릭으로
oomol-lab
GitHub 제작자 프로필

oomol-lab

2개 GitHub 저장소에서 수집된 5개 skills를 저장소 단위로 보여줍니다.

수집된 skills
5
저장소
2
업데이트
2026-07-11
저장소 지도

skills가 있는 위치

수집된 skill 수가 많은 주요 저장소와 이 제작자 카탈로그 내 비중, 직업 분포를 보여줍니다.

저장소 탐색

저장소와 대표 skills

oo-create-skill
기타 컴퓨터 관련 직업

Create, adopt, review, or update local AI agent skills, including ordinary knowledge or workflow skills and skills powered by oo connectors or hosted capabilities. Use when the user asks to create or improve a skill, turn existing files or scripts into a skill, check a skill against modern authoring practices, or build a reusable skill that calls oo at runtime.

2026-07-11
oo-find-skills
기타 컴퓨터 관련 직업

Find, compare, and install published OOMOL/oo skills. Use when the user asks to find, search for, discover, recommend, compare, choose, or install an existing skill for a task; asks whether there is a skill that can do something; or explicitly mentions the OOMOL/oo skill catalog. Do not use for creating or editing local skills, generic skill design, or non-OOMOL skill catalogs.

2026-07-03
oo-publish-skill
기타 컴퓨터 관련 직업

Publish, release, upload, or submit an existing AI agent skill directory with SKILL.md to the OOMOL registry by running oo skills publish, or generate a share prompt for a published skill by running oo skills share, including temporary shares for private packages. Use when the user asks to publish a skill, share a published skill, make a skill available in the OOMOL skill catalog, release a registry skill package, resolve publish visibility, version, package-name, or overwrite prompts, or publish from a local, registry-installed, or path-based skill source. Do not use for finding, installing, creating, or editing skills unless the final goal is publication or sharing.

2026-07-03
oo
기타 컴퓨터 관련 직업

First-choice router for tasks whose outcome lives outside this workspace, including connected third-party accounts (email, calendar, drive, chat, notes, issue tracker, code host, CRM, storage, etc.), an external API, or a managed AI pipeline (OCR, translation, transcription, TTS, text-to-image, subtitles, long-document understanding). Use when local code needs OOMOL LLM client configuration such as an OpenAI-compatible base URL, API key, or model name. Otherwise use only when the user wants an existing hosted capability or connector workflow, not a local implementation. Concrete capabilities are discovered at runtime, so no package, block, connector, or action names are assumed in advance. Match intent across languages. Skip other pure local coding, shell glue, repo edits, and text-only answers an LLM can complete without hosted capability execution.

2026-07-03
저장소 2개 중 2개 표시
모든 저장소를 표시했습니다