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From dotnet-skills
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends OpenCode's capabilities with specialized knowledge, workflows, or tool integrations.
npx claudepluginhub wshaddix/dotnet-skillsHow this skill is triggered — by the user, by Claude, or both
Slash command
/dotnet-skills:skill-creatorThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
This skill provides guidance for creating effective skills.
Searches USPTO patent and trademark records from official APIs including PatentSearch, TSDR, and assignment databases.
Share bugs, ideas, or general feedback.
This skill provides guidance for creating effective skills.
Skills are modular, self-contained packages that extend OpenCode's capabilities by providing specialized knowledge, workflows, and tools. Think of them as "onboarding guides" for specific domains or tasks—they transform OpenCode from a general-purpose agent into a specialized agent equipped with procedural knowledge that no model can fully possess.
The context window is a public good. Skills share the context window with everything else OpenCode needs: system prompt, conversation history, other Skills' metadata, and the actual user request.
Default assumption: OpenCode is already very smart. Only add context OpenCode doesn't already have. Challenge each piece of information: "Does OpenCode really need this explanation?" and "Does this paragraph justify its token cost?"
Prefer concise examples over verbose explanations.
Match the level of specificity to the task's fragility and variability:
High freedom (text-based instructions): Use when multiple approaches are valid, decisions depend on context, or heuristics guide the approach.
Medium freedom (pseudocode or scripts with parameters): Use when a preferred pattern exists, some variation is acceptable, or configuration affects behavior.
Low freedom (specific scripts, few parameters): Use when operations are fragile and error-prone, consistency is critical, or a specific sequence must be followed.
Think of OpenCode as exploring a path: a narrow bridge with cliffs needs specific guardrails (low freedom), while an open field allows many routes (high freedom).
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)
│ │ └── compatibility: (optional, rarely needed)
│ └── 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.)
Every SKILL.md consists of:
name and description fields (required), plus optional fields like license, metadata, and compatibility. Only name and description are read by OpenCode to determine when the skill triggers, so be clear and comprehensive about what the skill is and when it should be used. The compatibility field is for noting environment requirements (target product, system packages, etc.) but most skills don't need it.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 OpenCode'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 OpenCode produces.
assets/logo.png for brand assets, assets/slides.pptx for PowerPoint templates, assets/frontend-template/ for HTML/React boilerplate, assets/font.ttf for typographyA skill should only contain essential files that directly support its functionality. Do NOT create extraneous documentation or auxiliary files, including:
The skill should only contain the information needed for an AI agent to do the job at hand. It should not contain auxilary context about the process that went into creating it, setup and testing procedures, user-facing documentation, etc. Creating additional documentation files just adds clutter and confusion.
Skills use a three-level loading system to manage context efficiently:
Keep SKILL.md body to the essentials and under 500 lines to minimize context bloat. Split content into separate files when approaching this limit. When splitting out content into other files, it is very important to reference them from SKILL.md and describe clearly when to read them, to ensure the reader of the skill knows they exist and when to use them.
Key principle: When a skill supports multiple variations, frameworks, or options, keep only the core workflow and selection guidance in SKILL.md. Move variant-specific details (patterns, examples, configuration) into separate reference files.
Pattern 1: High-level guide with references
# PDF Processing
## Quick start
Extract text with pdfplumber:
[code example]
## Advanced features
- **Form filling**: See [FORMS.md](FORMS.md) for complete guide
- **API reference**: See [REFERENCE.md](REFERENCE.md) for all methods
- **Examples**: See [EXAMPLES.md](EXAMPLES.md) for common patterns
OpenCode loads FORMS.md, REFERENCE.md, or EXAMPLES.md only when needed.
Pattern 2: Domain-specific organization
For Skills with multiple domains, organize content by domain to avoid loading irrelevant context:
bigquery-skill/
├── SKILL.md (overview and navigation)
└── reference/
├── finance.md (revenue, billing metrics)
├── sales.md (opportunities, pipeline)
├── product.md (API usage, features)
└── marketing.md (campaigns, attribution)
When a user asks about sales metrics, OpenCode only reads sales.md.
Similarly, for skills supporting multiple frameworks or variants, organize by variant:
cloud-deploy/
├── SKILL.md (workflow + provider selection)
└── references/
├── aws.md (AWS deployment patterns)
├── gcp.md (GCP deployment patterns)
└── azure.md (Azure deployment patterns)
When the user chooses AWS, OpenCode only reads aws.md.
Pattern 3: Conditional details
Show basic content, link to advanced content:
# DOCX Processing
## Creating documents
Use docx-js for new documents. See [DOCX-JS.md](DOCX-JS.md).
## Editing documents
For simple edits, modify the XML directly.
**For tracked changes**: See [REDLINING.md](REDLINING.md)
**For OOXML details**: See [OOXML.md](OOXML.md)
OpenCode reads REDLINING.md or OOXML.md only when the user needs those features.
Important guidelines:
Example: Splitting a long skill into references
When a skill exceeds 500 lines, split detailed content into separate reference files:
csharp-coding-standards/
├── SKILL.md (273 lines - overview and principles)
└── reference/
├── language-patterns.md (457 lines - detailed language examples)
├── performance-patterns.md (261 lines - Span<T>, Memory<T>, async patterns)
├── api-design.md (180 lines - API design principles and best practices)
├── error-handling.md (114 lines - Result type patterns)
└── anti-patterns.md (284 lines - anti-patterns and reflection warnings)
In SKILL.md, reference these files:
## Language Patterns
For detailed examples of records, value objects, pattern matching, and nullable reference types, see [reference/language-patterns.md](reference/language-patterns.md).
## Performance Patterns
For Span<T>, Memory<T>, and async/await best practices, see [reference/performance-patterns.md](reference/performance-patterns.md).
## API Design
For comprehensive API design guidelines, see [reference/api-design.md](reference/api-design.md).
## Error Handling
For Result type patterns and railway-oriented programming, see [reference/error-handling.md](reference/error-handling.md).
## Anti-Patterns
For patterns to avoid and reflection warnings, see [reference/anti-patterns.md](reference/anti-patterns.md).
Skill creation involves these steps:
Follow these steps in order, skipping 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.
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 OpenCode to use. Include information that would be beneficial and non-obvious to OpenCode. Consider what procedural knowledge, domain-specific details, or reusable assets would help another OpenCode instance execute these tasks more effectively.
Consult these helpful guides based on your skill's needs:
These files contain established best practices for effective skill design.
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/.
Added scripts must be tested by actually running them to ensure there are no bugs and that the output matches what is expected. If there are many similar scripts, only a representative sample needs to be tested to ensure confidence that they all work while balancing time to completion.
Any example files and directories not needed for the skill should be deleted. The initialization script creates example files in scripts/, references/, and assets/ to demonstrate structure, but most skills won't need all of them.
Writing Guidelines: Always use imperative/infinitive form.
Write the YAML frontmatter with name and description:
name: The skill namedescription: This is the primary triggering mechanism for your skill, and helps OpenCode understand when to use the skill.
docx skill: "Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when OpenCode needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks"Do not include any other fields in YAML frontmatter.
Example of proper frontmatter:
---
name: csharp-coding-standards
description: Write modern, high-performance C# code using records, pattern matching, value objects, async/await, Span<T>/Memory<T>, and best-practice API design patterns. Use when writing new C# code or refactoring existing code, designing public APIs for libraries or services, optimizing performance-critical code paths, or building async/await-heavy applications.
---
Fields that should NOT be included:
invocable - Not a valid fieldversion - Not a valid fieldtags - Not a valid fieldlast-updated - Not a valid fieldcolor - Not a valid fieldmodel - Not a valid fieldWriting good descriptions:
The description is the primary triggering mechanism for your skill. It should:
Good description examples:
# Good: Clear purpose + trigger phrases
description: Configure Akka.NET with .NET Aspire for local development and production deployments. Use when setting up Akka.NET with Aspire orchestration, configuring Akka.Cluster, integrating Akka.Persistence with SQL Server, or deploying to Kubernetes.
# Good: Technology focus + specific triggers
description: IHttpClientFactory patterns with Polly for retries, circuit breakers, timeouts, and resilient HTTP communication. Use when configuring resilient HTTP clients in ASP.NET Core, implementing retry policies with Polly, or setting up circuit breakers for external service calls.
# Good: Domain expertise + when to use
description: Entity Framework Core best practices including NoTracking by default, query splitting for navigation collections, migration management, dedicated migration services, and common pitfalls to avoid. Use when setting up EF Core in a new project, optimizing query performance, managing database migrations, or debugging change tracking issues.
Write instructions for using the skill and its bundled resources.
Once development of the skill is complete, it must be packaged into a distributable .skill 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 .skill file named after the skill (e.g., my-skill.skill) that includes all files and maintains the proper directory structure for distribution. The .skill file is a zip file with a .skill extension.
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: