Generate Qamus entry candidates, hover glosses, and morphological analysis for Arabic text.
npx skills add https://github.com/theislampill/fusha --skill fusha-sarf
Please help me install this Agent Skill. Skill: fusha-sarf Source: https://github.com/theislampill/fusha/tree/main/skills/sarf Command: npx skills add https://github.com/theislampill/fusha --skill fusha-sarf
This Skill automates the complex process of generating and managing Arabic linguistic intelligence, simplifying the creation of Qamus entries, hover glosses, and morphological analysis.
To generate Qamus candidates from a corpus, use the fusha-sarf skill with the corpus file 'arabic-corpus.txt'.
High-intent search queries and answers about installing and using this skill.
Morphological analysis on Arabic text is performed by generating root, form, part-of-speech, and clitic decisions for words. This process operates independently of external sources to derive linguistic insights directly from the provided text.
Generating Qamus entry candidates from an Arabic corpus requires processing the text file to automatically extract and manage linguistic intelligence. This allows you to build comprehensive dictionary entries directly from your source materials.
Hover glosses enhance Arabic language learning by providing immediate, inline definitions and morphological context for words. Authoring these glosses helps learners understand complex vocabulary and linguistic structures without leaving the text.
Yes, you can analyze Arabic linguistic features without external dependencies. The morphological analysis operates independently to process morphological features and generate linguistic insights using only the internal sarf engine and related resources.
To start Arabic morphological analysis and generate Qamus candidates, you need to provide a corpus file, such as 'arabic-corpus.txt'. The Skill processes this text file to extract morphological features and author hover glosses.
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