earnings quality research coach
by nowrich
Audit earnings reports to separate headline EPS beats from underlying financial quality and sustainability.
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Works with the AI tools you already use
See it in action
You say
Analyze NVDA's latest earnings report. They beat EPS by $0.12 and revenue by $200M. Here is the transcript and the 10-Q data. Is this a high-quality beat?
Your agent does
Earnings Quality Scorecard
| Category | Assessment | Quality Rating | | -------- | ---------- | -------------- | | Revenue | 15% organic growth driven by Data Center volume. | Strong | | Cash Flow | OCF/Net Income at 110%; no receivables bloat. | Strong | | One-Time Items | $50M tax credit accounted for $0.03 of the beat. | Neutral |
Verdict: High Quality. Growth is volume-driven with clean cash conversion.
What you get
About this skill
The problem
Traders often get trapped by "headline beats" where a company meets EPS estimates through accounting tricks, tax credits, or cost-cutting rather than actual growth. Distinguishing between sustainable performance and one-time financial engineering is difficult during the high-pressure earnings window.
What it does
- Analyzes revenue quality by looking at volume, pricing, and organic vs. acquisition-driven growth.
- Audit margins to identify if beats are driven by pricing power or temporary non-operating income.
- Reconciles operating cash flow against net income to spot inventory piling or receivables issues.
- Evaluates guidance raises against new quarterly run-rates to verify management optimism.
- Quantifies the impact of one-time items like litigation charges, FX tailwinds, and stock-based compensation.
Why this beats prompting it yourself
General LLM prompts often focus on sentiment or summary. This skill enforces a rigorous financial framework that treats adjusted EPS with skepticism and mandates cash flow reconciliation, preventing the agent from simply parroting investor relations' talking points.
Use cases
- Vetting a post-earnings stock jump before entering a long position.
- Comparing two competitors that both reported beats to see which has durable momentum.
- Identifying "earnings traps" where high headline numbers mask deteriorating fundamentals.
- Preparing a quality-focused briefing for a portfolio review or investment committee.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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