WeChat Investment Blogger Distiller
Paste the following prompt into your AI chat to install this skill:
Follow https://skillhub.cn/install/skillhub.md to install @redfox-data/investor-distiller.
About this skill
Problem
WeChat investment bloggers spread their views across many posts. Manual review can miss stock aliases, sector emphasis, and argumentation chains. Simple keyword frequency captures surface terms but not how a blogger evaluates opportunities. This skill compresses historical posts into a comparable seven-dimensional style profile for research, writing reference, and style simulation, not direct buy/sell advice.
How It Works
After an account ID and article tier are provided, the pipeline roughly does the following:
- Collection: paginated UUID retrieval, then per-post fetch of body, summary, and word-cloud data into output/{name}/.
- Distillation: raw full-text extraction for stocks, sectors, terms, title structure, and tone markers; deeper detection of analysis tools, argumentation patterns, cross-market perspective, and philosophy.
- Profile: covers trading system, market judgment, expression style, depth, interaction, hot topics, and persona.
- Validation: weighted checks for stocks, style, and system; style simulation is allowed only after the threshold is met.
- Simulation: generates stock or market commentary with fixed data-source limits and “AI style simulation, not investment advice” disclaimers.
Boundaries
It fits structured study, style reference, and AI simulation. Quality depends on collected completeness: 20 articles is rougher, 100 is more stable. It is not a real-time market feed or an advisor; live market data requires external sources, and original views must be separated from AI distilled conclusions.
Use Cases
- When studying a WeChat finance account, extract 60 posts into stock, sector, tone, and argumentation profiles.
- Before writing investment commentary, validate a blogger's trading system, market view, and structure for consistency.
- Compare short-term and long-term bloggers by tools, holding period, data density, and cross-market perspective.
- Generate a style-simulation analysis with data-source limits and a not-investment-advice disclaimer.
Best For
- Investment content analysts who need to structure stock mentions, sector focus, and argumentation chains from posts.
- Finance editors who need to compare expression structure, tone, and title/opening/closing patterns.
- Writing-model engineers who need confidence-labeled style features, thinking-layer traits, and validation results.
- Behavioral data analysts who need short/long-term branching for data citation and cross-market perspective.
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