Convert Gooaye podcast transcripts into evidence-based investment and life decision frameworks.
npx skills add https://github.com/thtang/alpha-persona-lab --skill gooaye
Please help me install this Agent Skill. Skill: gooaye Source: https://github.com/thtang/alpha-persona-lab/tree/main/gooaye Command: npx skills add https://github.com/thtang/alpha-persona-lab --skill gooaye
This Skill turns Gooaye/股癌 podcast transcripts into structured, evidence-based investment and life/QA worldviews, so you can answer questions with corpus-wide logic and episode-date market alignment instead of repeating quotes.
Run the Gooaye skill to answer by automatically syncing the latest local sources, then using distilled episode notes and corpus retrieval to respond.
High-intent search queries and answers about installing and using this skill.
You extract investment reasoning from podcast transcripts by syncing canonical transcript sources daily and applying evidence-driven distillation. This process aligns episode dates with market regime snapshots to answer ticker or sector questions using corpus-wide logic.
Evidence-based decision framework distillation converts raw podcast transcripts into structured notes-first reasoning. It prioritizes canonical per-episode distillation outputs and falls back to guided transcript processing only when notes are missing.
Yes, you can optionally run ASR fallback for missing episodes during daily corpus sync. This ensures local canonical transcripts and SoundOn RSS metadata remain comprehensive when source feeds are unreachable or stale.
The best way to retrieve life and relationship Q&A worldviews is through corpus-wide retrieval of recurring frameworks. This captures recurring relationship, career, family, and mental load decision frameworks from distilled episode notes.
Transcript distillation requires non-impersonation posture to prevent generating quotes as the host, while market alignment maps episode dates to market regime snapshots. This ensures ticker or sector analysis reflects the exact context discussed.
No, aggressive mode only changes the output style to a decisive trade call. It explicitly preserves the same evidence-driven reasoning standards and non-impersonation posture required by the distilled notes-first retrieval process.
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