earnings quality research coach

    by nowrich

    1

    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

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLI+17 more

    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

    Identify if EPS beats are driven by tax credits or buybacks.Verify if revenue growth is organic or inflated by discounting.Compare operating cash flow to net income to spot accounting red flags.Assess if management guidance is realistically supported by the current run-rate.

    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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