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Multiplat Research

Multi-platform channel/video batch research — enumerate a creator's latest N items on YouTube, Bilibili, or local files (including Douyin creator-center exports), fetch text with captions first and local ASR as fallback, then write ONE cross-video report instead of N isolated summaries.

What is Multiplat Research?

Multiplat Research is a comprehensive batch research skill designed for AI agents like Claude Code, Cursor, or Codex. It allows developers and researchers to analyze a creator's latest content across multiple platforms (YouTube, Bilibili, and local files, including Douyin creator-center exports) in a single workflow. Instead of generating separate summaries per video, this skill aggregates text from captions (preferred) or local ASR fallback for each item, then produces a unified cross-video report. This is highly useful for competitor tracking, channel research, content strategists, and data analysts who need efficient multi-platform analysis. The skill is triggered by natural language phrases such as 'batch research this channel' or 'analyze Bilibili UP master's latest videos'.

Works with~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/xichow0663-gif/multiplat-research/tree/master
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What does Multiplat Research do?

Multi-platform channel/video batch research — enumerate a creator's latest N items on YouTube, Bilibili, or local files (including Douyin creator-center exports), fetch text with captions first and local ASR as fallback, then write ONE cross-video report instead of N isolated summaries.

Trigger phrases: batch research this channel, channel's recent videos, batch summarize YouTube, analyze Bilibili UP master, YouTube channel research, competitor channel tracking, Douyin account data review, multi-platform content research, channel research, batch summari

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