This project packages the public research and analytical framework of AI/semiconductor supply-chain analyst @aleabitoreddit into a self-contained, installable agent skill. It targets technically savvy users seeking a differentiated approach to evaluating US stock ideas, focusing on identifying upstream supply-chain bottlenecks and mispriced opportunities often overlooked by mainstream analysis. The primary benefit is a structured, actionable lens derived from expert public commentary, designed to foster deeper research rather than direct trade replication.

How It Works

The repository distills over 5,800 tweets and several long-form articles into a comprehensive research artifact. It employs a core methodology of tracing hyperscaler capital expenditure upstream into critical supply-chain chokepoints—such as optical components, compound semiconductors, memory, and power infrastructure—where smaller, potentially mispriced market-cap companies may offer significant leverage. This analytical lens is packaged as a ready-to-use agent skill, enabling users to apply the analyst's framework to new stock ideas and existing theses.

Quick Start & Requirements

• Install: npx skills add yan-labs/serenity-aleabitoreddit or by copying the repository folder into an agent's skills directory.
• Prerequisites: Node.js (for npx), Python 3 (for data processing scripts prep.py, update.py).
• Data: Includes raw tweet archives (.json, .csv), article summaries, and derived analysis files.
• Links: SKILL.md details the agent skill's workflows and risk framing; methodology.md outlines the analyst's transferable principles.

Highlighted Details

• Synthesizes data from 5,857 tweets (spanning July 2025 - June 2026) and 4 X Articles (Jan - May 2026).
• Focuses on identifying "chokepoint" suppliers rather than obvious market leaders, targeting mispriced small/micro-cap opportunities.
• Provides a structured framework with named principles, per-ticker knowledge bases, and a chronological track record.
• Includes Python scripts for data preparation and incremental updates from new posts.

Maintenance & Community

Maintenance rules for incrementally distilling new posts are documented. The repository is presented as an independent research artifact, with no explicit affiliation or community channels (e.g., Discord, Slack) mentioned.

Licensing & Compatibility

The repository's license is not explicitly stated in the provided README, which requires clarification for adoption decisions. It is designed as an agent skill, implying compatibility with agent-based systems. The underlying data consists of publicly available tweets and articles.

Limitations & Caveats

This tool is strictly for decision support and is not financial advice; it does not execute trades. The analyst's self-reported returns are unverified and subject to survivorship bias. The focus is on volatile micro/small-cap stocks. The framework is intended to aid question-asking, not to guide direct trade copying. Full article texts are intentionally omitted.