Hebrew nikud (vowel points) reference for AI agents. Correct nikud rules for verb conjugations (binyanim), dagesh, gender suffixes, homographs, and common mistakes. Use before adding nikud to Hebrew text, especially for TTS.
Trust score 78/100 (Trusted) · 30+ installs · 3 GitHub contributors · MIT license
AI agents adding nikud to Hebrew text often make critical errors: wrong binyan identification leads to incorrect vowel points, missing dagesh on loanwords causes mispronunciation, and over-nikuding degrades TTS quality rather than improving it.
npx skills-il add openclaw/skills/shaharsha/hebrew-nikud -a claude-codeThis is a community skill from an external source. The ZIP upload may not work on all platforms if the SKILL.md format is not fully compatible.
I have a Hebrew paragraph that will be read aloud by a TTS engine. Add selective nikud only where pronunciation is ambiguous. Focus on dagesh in begedkefet letters, homographs, and foreign names. Do not over-nikud.
Check the nikud on these Hebrew verbs. For each verb, identify the correct binyan and verify the vowel points match the conjugation pattern. Flag any errors where the wrong binyan nikud was applied.
I have a Hebrew text containing foreign names and loanwords. Add dagesh where needed to ensure correct pronunciation (P not F, B not V, K not Kh). List each word you changed and explain why.
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Generate SRT subtitles from video or audio files with Hebrew and English transcription support. Use when you need to create captions, transcripts, or hardcoded subtitles for social media and WhatsApp. Supports automatic language detection, translation between Hebrew and English, and burning subtitles directly into video files.
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