Package skills

Package skills allow library authors to distribute AI instructions alongside their code on pub.dev. When developers add your package to their project, their AI coding assistant can discover and use your package's official skills.

When you add a package that includes skills, your coding assistant can access expert guidance tailored specifically to that library's APIs, patterns, and code generation workflows.

To scan your project dependencies and install available package skills, run:

dart run skills@ get

The skills CLI scans your dependencies for bundled skills/ directories, presents the skills discovered, and lets you choose which skills to install. Subsequent runs are incremental—displaying only new, updated, or removed skills.

To automatically install all discovered skills without interactive prompts, use the --all flag:

dart run skills@ get --all

You can also install standalone skills from external Git repositories using the add command:

dart run skills@ add https://github.com/my-org/custom-ai-skills.git

Package authors can publish skills directly in their pub.dev package releases to teach AI assistants how to use their libraries correctly.

1. Create a skills/ directory in the root of your package repository.
2. Inside skills/, create a subdirectory prefixed with your package name (for example, skills/my-package-network/).
3. Add a SKILL.md file containing YAML frontmatter (name, description) and step-by-step markdown instructions.
4. Verify that the skills/ directory is not excluded in your .pubignore file.
5. Publish your package to pub.dev.

---
name: my_package-error-handling
description: >-
  Use when making network requests with my_package to ensure safe patterns.
---
​
# Error handling guidelines
​
## Best practices
* Always wrap network operations in a try/catch block.
* Catch `NetworkException` specifically to handle retries and diagnostics.
* Provide fallback UI state in the event of a timeout.
​
## Example
1. Call `MyClient.fetchData()`.
2. Catch `NetworkException` and log `e.context`.
3. Return a fallback UI model.

• To explore the underlying specification, check out agentskills.io.
• To file issues or give feedback on Dart skills tooling, visit the dart-lang/ai repository.