Tech Earnings Deepdive

This is a comprehensive framework for analyzing tech company earnings reports like you're running your own investment firm. It walks you through 16 analysis modules covering everything from revenue quality and cash flow to competitive positioning and management credibility, then filters the findings through six different investment philosophies (growth, value, quality, etc.) to stress test your thesis. The standout feature is the "key forces" approach: instead of mechanically grinding through every checklist item, you identify the 1-3 decisive factors that will actually move the stock over 3-5 years, then allocate your analysis time accordingly. It pushes you toward primary sources (SEC filings, Glassdoor reviews, customer feedback) rather than recycled analyst summaries, and ends with actionable position sizing decisions, not vague bull/bear calls. Heavy but thorough if you're seriously evaluating a tech position.

skills.sh installs: 539
GitHub stars: 1.1K
last updated: Aug 21, 2026

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Install

$ npx -y skills add star23/day1global-skills --skill tech-earnings-deepdive --agent claude-code

Installs into .claude/skills of the current project.

Files

Tech Stock Earnings Deep Dive Analysis & Multi-Perspective Investment Memo v3.0

Positioning & Design Philosophy

You are providing institutional-grade earnings analysis services for a "large retail investor" — someone investing their own capital, with no LPs, who holds tech stock positions on a quarterly and annual basis.

Core design principles:

Key Forces Driven: First identify 1-3 decisive forces, then prioritize the 16 modules around those forces — deeply examine related modules, provide standard coverage for the rest
Multi-Philosophy Confrontation: Review the same dataset through 6 completely different investment worldviews, letting conclusions emerge from the collision
Primary Evidence First: Third-party aggregation sites are the floor, not the ceiling — trace information back to its source
Actionable Decisions: Not "bullish/bearish," but "at what price take what action, what conditions trigger an exit"
Quarterly Tracking Design: Each module has built-in QoQ and YoY comparison frameworks to support continuous cross-quarter tracking