본문으로 건너뛰기
cccskills
무료GitHub에 공개

skill-creator

Create or update skills. Use when designing, structuring, or packaging skills with scripts, references, and assets.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(4)

  • SKILL.md3.9 KB
  • scripts/init_skill.py13.4 KB
  • scripts/package_skill.py4.6 KB
  • scripts/quick_validate.py6.7 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Skill Creator

Guidance for creating effective skills.

About Skills

Skills are modular packages that extend agent capabilities with specialized knowledge, workflows, and tools. Each skill is a directory containing a SKILL.md file and optional bundled resources.

What Skills Provide

  1. Specialized workflows - Multi-step procedures for specific domains
  2. Tool integrations - Instructions for working with specific file formats or APIs
  3. Domain expertise - Project-specific knowledge, schemas, business logic
  4. Bundled resources - Scripts, references, and assets for complex and repetitive tasks

Skill Locations in AutoSwarm

AutoSwarm uses a two-level skill system:

LevelPathScope
System.opc/skills/<skill-name>/Shared across all projects
Project.opc/projects/<project_id>/skills/<skill-name>/Specific to one project

Project skills with the same name override system skills. When creating new skills from project experience, always use the project level.

How Skills Are Created

Skills enter the system through two paths:

  1. Agent-driven (this skill): You identify a pattern, read this guide, and create the skill manually using init_skill.py or file_write.
  2. Auto-promoted: The system automatically distills playbook skills from repeated project reflections (threshold: 2 reflections with recurring patterns). These are saved as <employee>-<role>-<domain>-playbook under the project skills directory.

Both paths produce the same <skill-name>/SKILL.md format. This guide covers the agent-driven path; auto-promoted skills follow the same naming and format conventions.

Core Principles

Concise is Key

The context window is shared. Only add context the agent doesn't already have. Prefer concise examples over verbose explanations.

Anatomy of a Skill

skill-name/
├── SKILL.md (required)
│   ├── YAML frontmatter (name, description required)
│   └── Markdown instructions
└── Bundled Resources (optional)
    ├── scripts/          - Executable code
    ├── references/       - Documentation loaded as needed
    └── assets/           - Files used in output

Progressive Disclosure

  1. Metadata (name + description) - Always in context (~100 words)
  2. SKILL.md body - When agent reads the skill (<5k words)
  3. Bundled resources - As needed (scripts can be executed without reading into context)

Naming

All skills — whether agent-created or auto-promoted — must follow these conventions:

  • Lowercase letters, digits, and hyphens only (e.g., backend-api-playbook)
  • Under 64 characters
  • Directory name must match the name field in frontmatter

Skill Creation Process

Step 1: Understand the skill with concrete examples

Clarify use cases: what triggers this skill, what does it produce?

Step 2: Plan reusable contents

Identify what scripts, references, and assets would help.

Step 3: Initialize the skill

For project-specific skills, create under .opc/projects/<project_id>/skills/:

python3 {baseDir}/scripts/init_skill.py <skill-name> --path .opc/projects/<project_id>/skills

Options: --resources scripts,references,assets and --examples.

Step 4: Edit the skill

Write SKILL.md with:

  • Frontmatter: name (hyphen-case, matches directory) and description (what it does + when to use it — this is the primary trigger for skill discovery)
  • Body: Instructions, examples, references to bundled resources

Step 5: Package (optional)

python3 {baseDir}/scripts/package_skill.py <path/to/skill-folder>

Validates the skill then creates a distributable .skill zip file.

Step 6: Iterate

Test, notice struggles, improve SKILL.md and resources.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

clawhub

무료

Search and install agent skills from ClawHub, the public skill registry. Use when needing new capabilities, searching for skills, installing skills, or updating installed skills.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

HKUDS/AutoSwarm1.9천2026년 10월 17일 업데이트

Standing rules for how any role in an AutoSwarm company coordinates with its peers — work-item discipline, messaging, meetings, and blocking collaboration. Loaded only in company_mode.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

HKUDS/AutoSwarm1.9천2026년 10월 17일 업데이트

cron

무료

Schedule reminders, recurring tasks, and one-time jobs using system crontab.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

HKUDS/AutoSwarm1.9천2026년 10월 17일 업데이트

github

무료

Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

HKUDS/AutoSwarm1.9천2026년 10월 17일 업데이트

memory

무료

Manage durable global/project memory in `.opc/memory/global.md` and `.opc/memory/projects/<current_project_id>.md`.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

HKUDS/AutoSwarm1.9천2026년 10월 17일 업데이트

Collaborate with other agents in AutoSwarm company mode via the `opc-collab` CLI — send messages, request user input, delegate work, read the manager board, respond in meetings, propose task adjustments.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

HKUDS/AutoSwarm1.9천2026년 10월 17일 업데이트

HKUDS의 스킬 모두 보기

이 스킬의 문제 신고