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Harryoung
Perfil de creador de GitHub

Harryoung

Vista por repositorio de 6 skills recopiladas en 1 repositorios de GitHub.

skills recopiladas
6
repositorios
1
actualizado
2026-01-17
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Repositorios principales por número de skills recopiladas, con su participación en este catálogo del creador y su variedad ocupacional.

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Repositorios y skills representativas

batch-notification
Desarrolladores de software

Send IM messages to users in batch. Used for notifying specific user groups, sending after table filtering, all-staff notifications, etc. Use this Skill when administrators request batch notifications, mass messaging, or notifications after table filtering. Trigger words: notify/send/mass + users/batch/table.

2026-01-17
document-conversion
Desarrolladores de software

Convert DOC/DOCX/PDF/PPT/PPTX documents to Markdown format. Automatically detect PDF type (electronic/scanned), extract images to separate directory. Use this Skill when administrator onboards non-Markdown documents. Trigger condition: Onboard DOC/DOCX/PDF/PPT/PPTX format files.

2026-01-17
expert-routing
Desarrolladores de software

Domain expert routing. When the knowledge base cannot answer user questions, find and notify the corresponding expert based on the question domain. Only available in IM mode. Trigger condition: No results in 6-stage retrieval.

2026-01-17
large-file-toc
Desarrolladores de software

Generate table of contents overview for large files. When onboarded Markdown file exceeds threshold (default 30KB), extract heading structure to create navigation file. Trigger condition: Markdown file size >= 30KB.

2026-01-17
satisfaction-feedback
Desarrolladores de software

Handle user satisfaction feedback. When users respond with "satisfied"/"unsatisfied", update FAQ usage count or record BADCASE. Trigger words: satisfied/unsatisfied/resolved/not resolved/thanks/满意/不满意/解决了/没解决/谢谢.

2026-01-17
excel-parser
Desarrolladores de software

Smart Excel/CSV file parsing with intelligent routing based on file complexity analysis. Analyzes file structure (merged cells, row count, table layout) using lightweight metadata scanning, then recommends optimal processing strategy - either high-speed Pandas mode for standard tables or semantic HTML mode for complex reports. Use when processing Excel/CSV files with unknown or varying structure where optimization between speed and accuracy is needed.

2026-01-06
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