| name | douyin-industry-video |
| description | Extract subtitles and metadata from Douyin or short-video links, then analyze investment or industry-chain claims in Chinese. Use when the user shares a Douyin/TikTok-style video link or downloaded video and asks to get complete subtitles, summarize the video, analyze AI/semiconductor/memory/order logic, identify who pays, judge cycle stage, or turn the workflow into reusable research. |
Douyin Industry Video
Use this skill to turn a short-video link into a verifiable transcript and an industry-research answer. Default to Chinese replies.
Workflow
- Read local project context first when available:
- Follow the current workspace's
AGENTS.md, CLAUDE.md, or equivalent instructions.
- If the user maintains a research vault or durable notes, read the relevant investing, industry-chain, AI hardware, memory, orders, or "who pays" notes before analysis.
- If no durable context exists, continue with the built-in framework in
references/analysis-framework.md.
- Fetch the video:
- For a Douyin URL, run
scripts/fetch_douyin_video.py <url> --out-dir work/video.
- If the user already provided a local video, skip fetch and use that file.
- Get subtitles in this order:
- Use official page metadata or subtitle fields if present.
- If there are burned-in subtitles, run
scripts/ocr_burned_subtitles.swift <video.mp4> <raw.jsonl> 1.
- Clean OCR with
scripts/clean_ocr_subtitles.py <raw.jsonl> <transcript.md> --json <transcript.json>.
- If OCR quality is weak and an OpenAI audio key or local
whisper CLI is available, transcribe audio and cross-check. Never print keys or save secrets.
- State transcript confidence:
- Say whether the transcript is official, audio-transcribed, or OCR-derived.
- For OCR, mark it as machine extracted from burned subtitles and note likely OCR errors.
- Analyze the video:
- Separate
video claim -> evidence -> inference -> risk.
- For industry-chain topics, use
天道产业链版 completeness: reality check, chain map, true bottleneck, company mapping, revenue/profit elasticity, event energy, falsification, tracking metrics, unresolved checks.
- For "AI chain all have orders / who pays" claims, apply the sponsor chain:
hyperscaler / AI cloud capex -> GPU / ASIC -> TSMC / advanced packaging -> HBM / server DRAM / SSD -> equipment / materials / power / optical interconnect.
- Memory closeout:
- If a reusable framework, trigger, or follow-up is created, update the user's configured durable memory or project notes when allowed.
- Do not store raw chat logs, secrets, account details, exact personal holdings, or irrelevant one-off content.
Practical Rules
- Do not pretend to have watched or transcribed a video if only metadata was available.
- Prefer direct evidence: transcript, official filings, earnings calls, company press releases, and current market data.
- Browse for current facts when the answer depends on recent financials, capex guidance, orders, prices, or stock-market moves.
- For investment answers, do not provide buy/sell instructions. Separate industry quality, cycle stage, valuation/timing, and position risk.
- Give numeric event energy when relevant, for example
短线事件能量 86/100，中期兑现能量 74/100.
Script Notes
fetch_douyin_video.py uses mobile user-agent HTML parsing and downloads the reflow video when Douyin exposes play_addr.ocr_burned_subtitles.swift uses macOS AVFoundation and Vision. It requires no global install but only works on macOS.clean_ocr_subtitles.py filters the subtitle band, deduplicates repeated OCR frames, and outputs Markdown plus optional JSON.
