Automate building and testing Alfred Script Filter workflows with the afwf SDK.
npx skills add https://github.com/MacHu-GWU/afwf_github-project --skill afwf
Please help me install this Agent Skill. Skill: afwf Source: https://github.com/MacHu-GWU/afwf_github-project/tree/main/.claude/skills/afwf Command: npx skills add https://github.com/MacHu-GWU/afwf_github-project --skill afwf
This guide helps developers build, modify, test, and deploy Alfred Script Filter workflows using the afwf SDK, reducing boilerplate and keeping references in one place.
Install afwf, define a ScriptFilter main function, and call send_feedback() to return items to Alfred.
High-intent search queries and answers about installing and using this skill.
You can build Alfred Script Filter workflows using Python by defining a ScriptFilter main function, implementing your logic, and calling send_feedback() to return items to Alfred. The afwf SDK handles the integration and reduces boilerplate.
The best way to structure an Alfred workflow is using a three-layer architecture: Python logic, a CLI entry point, and Alfred workflow config. This separation of concerns keeps your codebase clean and maintainable.
Yes, you can implement fuzzy matching and disk caching in Alfred workflows. The afwf SDK provides complete references and patterns for these common features, allowing you to enhance search performance and reduce redundant processing.
You test and package an Alfred workflow by following best practices for testing and logging, then configuring a publish-ready pyproject.toml entry point. The SDK-driven project structure supports standard Python packaging workflows.
Yes, the afwf SDK supports write actions. It provides complete references for common AFWF patterns including write actions, enabling your Python workflows to modify and update items directly within Alfred.
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