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stock-analysis

Integrate transcript NLP, tone signals, insider data, and risk frameworks for stock analysis.

Updated Aug 23, 2026
Search Tags:#investment#NLP#transcripts#analyze#risk#stocks#insider
One-click install
npx skills add https://github.com/jonathanwxh-cell/alyosha-workspace --skill stock-analysis-jonathanwxh-cell
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: stock-analysis
Source: https://github.com/jonathanwxh-cell/alyosha-workspace/tree/main/skills/stock-analysis
Command: npx skills add https://github.com/jonathanwxh-cell/alyosha-workspace --skill stock-analysis-jonathanwxh-cell

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a structured, qualitative view of stock analysis by integrating transcript NLP, tone signals, insider data, and risk frameworks to help users evaluate a stock, assess management quality, and guide investment decisions.

Core Features & Use Cases

  • Transcript NLP analysis: Derives tone signals, hedging, conviction, and guidance quality from earnings call transcripts.
  • Insider activity & analyst signals: Incorporates insider transactions and analyst recommendations to triangulate risk and conviction.
  • Risk framework integration: Applies industry-standard risk and fragility assessments to investment theses.
  • Use Case: Imagine evaluating a company after quarterly results; this Skill returns a structured qualitative view to inform buy/sell decisions and risk assessment.

Quick Start

Run the full stock-analysis workflow for ticker NVDA:

  • python3 scripts/transcript-compare.py NVDA --quarters 4
  • python3 scripts/deep-analyzer.py NVDA --transcript
  • python3 scripts/finnhub-client.py insider NVDA
  • python3 scripts/finnhub-client.py recommend NVDA

Frequently Asked Questions about stock-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze earnings call transcripts for stock investment signals?▼

Analyze earnings call transcripts by parsing tone signals, hedging, and conviction levels to evaluate management quality and guide investment decisions. This approach derives qualitative insights directly from transcript NLP.

What is the best way to combine insider transactions and risk frameworks for stock analysis?▼

Combine insider transaction data with industry-standard risk frameworks to triangulate investment conviction and fragility. Integrating these alternative data signals provides a structured qualitative view for buy or sell decisions.

Can I compare quarterly earnings transcripts to assess management guidance quality?▼

Yes, you can compare quarterly earnings transcripts to assess management guidance quality. Running a transcript comparison across multiple quarters derives tone signals and reveals shifts in conviction and hedging.

Does stock analysis from transcripts require an API key for insider data retrieval?▼

Retrieving insider data and analyst recommendations requires connecting to the Finnhub client. Using this data retrieval component incorporates insider transactions to triangulate risk within the investment thesis.

What are the limitations of using NLP tone signals for company evaluation?▼

NLP tone signals provide qualitative insights but should be triangulated with insider data and risk frameworks for reproducible company evaluation. Relying solely on transcript parsing limits risk assessment scope.

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