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private-company-research

Deep research framework for pre-IPO / private companies (Ant Group, SpaceX, Stripe, ByteDance...). Six analyst lenses — business model, financial forensics, competitive landscape, risk & governance, tech & IP, alternative-data signals — run in parallel via run_swarm, then cross-validated for signal consistency before any verdict. Built around the core challenge of private-company work: information is scarce, so every data point carries a confidence label (high / medium / low), inference is shown separately from fact, and 'I don't know' is a valid output. Outputs a fair-value range, exit-path analysis, and an information-gap map. Use for any unlisted company where you need to judge what the business is actually worth.

67

Quality

81%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Low

Low-risk findings.

1 low severity finding. Worth noting, but not necessarily harmful.

Low

W011: Third-party content exposure detected (indirect prompt injection risk).

What this means

The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.

Why it was flagged

The required runtime workflow is a multi-source private-company research flow that explicitly expects ingesting external web/app/social/registry content (e.g., “LinkedIn/Boss/Indeed”, “App Store/七麦/SimilarWeb”, “Weibo/Zhihu/Xiaohongshu/X/Reddit”, “天眼查/企查查”), which are outsider-authored free text that would be fed into the agent’s LLM context via retrieval/scraping during research.

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Repository
HKUDS/Vibe-Trading
Audited
Security analysis
Snyk

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