메뉴
Orchestrator skill for creating effective skills. Guides through 6 steps - understanding examples, planning contents with scope assessment, initialization, editing with contracts, packaging, and iteration. Use when creating a new skill or updating an existing skill.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | skill-creator |
| description | Orchestrator skill for creating effective skills. Guides through 6 steps - understanding examples, planning contents with scope assessment, initialization, editing with contracts, packaging, and iteration. Use when creating a new skill or updating an existing skill. |
| skill_type | orchestrator |
| license | Complete terms in LICENSE.txt |
This skill provides guidance for creating effective skills.
Inputs:
Outputs:
Success Criteria:
Skills are modular, self-contained packages that extend Claude's capabilities by providing specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific domains or tasks—they transform Claude from a general-purpose agent into a specialized agent equipped with procedural knowledge that no model can fully possess.
Every skill consists of a required SKILL.md file and optional bundled resources:
skill-name/
├── SKILL.md (required)
│ ├── YAML frontmatter metadata (required)
│ │ ├── name: (required)
│ │ └── description: (required)
│ └── Markdown instructions (required)
└── Bundled Resources (optional)
├── scripts/ - Executable code (Python/Bash/etc.)
├── references/ - Documentation intended to be loaded into context as needed
└── assets/ - Files used in output (templates, icons, fonts, etc.)
Skill names use category prefixes for organization. The prefix indicates the skill's domain.
| Prefix | Category | Examples |
|---|---|---|
db- | Database | db-postgres, db-sqlite |
auth- | Authentication | auth-better-auth, auth-lucia |
infra- | Infrastructure & deployment | infra-railway, infra-docker, infra-env |
ui- | Frontend & design | ui-design-system, ui-principles |
state- | State management | state-effector, state-tanstack |
tools- | External integrations | tools-linear, tools-email, tools-youtube |
secrets- | Secrets management | secrets-1password |
| (none) | Core workflow skills | feature-build, skill-creator, judge |
Framework skills use the framework name first: nextjs-16, react-19
Naming rules:
my-skill-nameMetadata Quality: The name and description in YAML frontmatter determine when Claude will use the skill. Be specific about what the skill does and when to use it. Use the third-person (e.g. "This skill should be used when..." instead of "Use this skill when...").
scripts/)Executable code (Python/Bash/etc.) for tasks that require deterministic reliability or are repeatedly rewritten.
scripts/rotate_pdf.py for PDF rotation tasksreferences/)Documentation and reference material intended to be loaded as needed into context to inform Claude's process and thinking.
references/finance.md for financial schemas, references/mnda.md for company NDA template, references/policies.md for company policies, references/api_docs.md for API specificationsassets/)Files not intended to be loaded into context, but rather used within the output Claude produces.
assets/logo.png for brand assets, assets/slides.pptx for PowerPoint templates, assets/frontend-template/ for HTML/React boilerplate, assets/font.ttf for typographySkills use a three-level loading system to manage context efficiently:
*Unlimited because scripts can be executed without reading into context window.
For most simple skills, skip this section - just build what you need. For complex workflows, consider whether the skill should be atomic or an orchestrator.
Atomic skills do ONE thing well with clear boundaries. They:
Examples: db-postgres, auth-better-auth, email-resend, docker-local
Orchestrator skills coordinate multiple phases or compose atomic skills. They:
Examples: feature-build, project-setup
To determine skill type, ask:
Complexity belongs in orchestration, not in individual skills.
Atomic skills that try to do too much become brittle and hard to compose. When in doubt, split into smaller atomic skills and create an orchestrator to coordinate them.
For detailed patterns on composing skills, see references/orchestration-patterns.md.
To create a skill, follow the "Skill Creation Process" in order, skipping steps only if there is a clear reason why they are not applicable.
Skip this step only when the skill's usage patterns are already clearly understood. It remains valuable even when working with an existing skill.
To create an effective skill, clearly understand concrete examples of how the skill will be used. This understanding can come from either direct user examples or generated examples that are validated with user feedback.
For example, when building an image-editor skill, relevant questions include:
To avoid overwhelming users, avoid asking too many questions in a single message. Start with the most important questions and follow up as needed for better effectiveness.
Conclude this step when there is a clear sense of the functionality the skill should support.
Before diving into implementation details, assess the skill's scope:
Is this a single focused task or a multi-step workflow?
If multi-step, can the phases be executed independently?
To turn concrete examples into an effective skill, analyze each example by:
Example: When building a pdf-editor skill to handle queries like "Help me rotate this PDF," the analysis shows:
scripts/rotate_pdf.py script would be helpful to store in the skillExample: When designing a frontend-webapp-builder skill for queries like "Build me a todo app" or "Build me a dashboard to track my steps," the analysis shows:
assets/hello-world/ template containing the boilerplate HTML/React project files would be helpful to store in the skillExample: When building a big-query skill to handle queries like "How many users have logged in today?" the analysis shows:
references/schema.md file documenting the table schemas would be helpful to store in the skillTo establish the skill's contents, analyze each concrete example to create a list of the reusable resources to include: scripts, references, and assets.
At this point, it is time to actually create the skill.
Skip this step only if the skill being developed already exists, and iteration or packaging is needed. In this case, continue to the next step.
When creating a new skill from scratch, always run the init_skill.py script. The script conveniently generates a new template skill directory that automatically includes everything a skill requires, making the skill creation process much more efficient and reliable.
Usage:
scripts/init_skill.py <skill-name> --path <output-directory>
The script:
scripts/, references/, and assets/After initialization, customize or remove the generated SKILL.md and example files as needed.
When editing the (newly-generated or existing) skill, remember that the skill is being created for another instance of Claude to use. Focus on including information that would be beneficial and non-obvious to Claude. Consider what procedural knowledge, domain-specific details, or reusable assets would help another Claude instance execute these tasks more effectively.
To begin implementation, start with the reusable resources identified above: scripts/, references/, and assets/ files. Note that this step may require user input. For example, when implementing a brand-guidelines skill, the user may need to provide brand assets or templates to store in assets/, or documentation to store in references/.
Also, delete any example files and directories not needed for the skill. The initialization script creates example files in scripts/, references/, and assets/ to demonstrate structure, but most skills won't need all of them.
Writing Style: Write the entire skill using imperative/infinitive form (verb-first instructions), not second person. Use objective, instructional language (e.g., "To accomplish X, do Y" rather than "You should do X" or "If you need to do X"). This maintains consistency and clarity for AI consumption.
To complete SKILL.md, answer the following questions:
For multi-phase workflows or skills that will be composed with others, consider adding a Contract section that defines clear boundaries:
## Contract
**Inputs:**
- [What the skill needs to begin - files, context, user input]
**Outputs:**
- [What the skill produces when complete]
**Success Criteria:**
- [ ] [Testable condition that indicates successful completion]
When to add a contract:
When to skip:
Once the skill is ready, it should be packaged into a distributable zip file that gets shared with the user. The packaging process automatically validates the skill first to ensure it meets all requirements:
scripts/package_skill.py <path/to/skill-folder>
Optional output directory specification:
scripts/package_skill.py <path/to/skill-folder> ./dist
The packaging script will:
Validate the skill automatically, checking:
Package the skill if validation passes, creating a zip file named after the skill (e.g., my-skill.zip) that includes all files and maintains the proper directory structure for distribution.
If validation fails, the script will report the errors and exit without creating a package. Fix any validation errors and run the packaging command again.
After testing the skill, users may request improvements. Often this happens right after using the skill, with fresh context of how the skill performed.
Iteration workflow:
Use when working with mise - creating/editing mise.toml or .mise.toml files, defining tasks with usage field arguments, managing dev tools and environments, configuring hooks, or when user mentions mise configuration.
Prisma 7 ORM with PostgreSQL — schema design, migrations, seeding, and Railway deployment patterns. This skill should be used when setting up Prisma in a new project, writing migrations, managing database schemas, or deploying Prisma-backed services to Railway.
Railway deployment and infrastructure management skill. This skill should be used when deploying applications to Railway, managing Railway services, checking deployment status, viewing logs, configuring environment variables, or troubleshooting Railway deployments.
NestJS 11 backend patterns with Fastify, modular architecture, guards, pipes, and Railway deployment. This skill should be used when building NestJS APIs, setting up backend services, or creating REST/GraphQL endpoints with NestJS.
shadcn/studio component library with MCP integration, theme generation, and block patterns. This skill should be used when building UI with shadcn components, selecting dashboard layouts, or generating landing pages. Canonical source for all shadcn-based work.
Theme generation with tweakcn for shadcn/ui and Magic UI animations. Use when setting up project themes, customizing color schemes, adding dark mode, or integrating animated components.