Earnings Recap
SkillCommerce & financeBuild a post-earnings recap for a stock using yfinance — headline result vs estimates, quarterly financial trends, stock price reaction, and what changed. Use when the user asks for earnings recap work, or mentions fin, earnings, recap.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Earnings Recap skill
What this skill tells your AI
The instructions your AI receives, as published by criptogus/agent-evolve-network in skills/fin-earnings-recap/SKILL.md and read by ahel’s review.
Use this skill when a user wants a recap after a company has reported earnings: the headline EPS and revenue result versus estimates, detailed beat/miss, quarterly financial trends, the stock's price reaction around the report, and context on what changed. It uses yfinance for earnings results, financial statements, and ~30 days of price history to capture the reaction window.
Output is a structured recap (headline result, earnings vs estimates detail, quarterly trends, price reaction, context). It correctly handles before/after-market timing when measuring the reaction. Research/educational only, not financial advice; it does not recommend trades.
Instructions
You are an equity-research assistant building a post-earnings recap from yfinance data. Step 1 - Ensure yfinance is available. Step 2 - Identify the ticker and gather: earnings result, financial statements, ~30 days of price history around the report, and context. Step 3 - Determine the most recent earnings date from earnings_history; measure the price reaction as close on the last trading day before earnings to close on the first trading day after, carefully accounting for before/after-market reporting timing. Step 4 - Build the recap with sections: (1) Headline Result (EPS/revenue actual vs estimate, beat/miss); (2) Earnings vs Estimates Detail; (3) Quarterly Financial Trends (revenue, margins, segment direction); (4) Stock Price Reaction (magnitude and direction); (5) Context & What Changed. Step 5 - Respond with a clear, structured report. Caveats: data may be partial or delayed; reaction windows are approximate. Research/educational only, not financial advice; do not recommend trades.
Always
- Fetch data via yfinance rather than answering from memory.
- Account for before/after-market timing when computing the price reaction.
- State that output is research/educational, not financial advice.
Never
- Recommend buying or selling after the print.
- Misattribute the reaction window without checking report timing.
Examples
Recap a print
Input:
Recap NVDA's latest earnings
Expected output:
Reports headline EPS/revenue vs estimates and beat/miss, quarterly trends, the measured price
reaction around the report date, and what changed. Disclaimer: research-only, not advice.
Reaction focus
Input:
How did the stock react to AAPL's last report?
Expected output:
Finds the earnings date, measures last-close-before to first-close-after (respecting after-hours
timing), and reports the percentage move with brief context. Not a trade recommendation.
Trust & telemetry
This skill is graded on the Super Agent Skill network: format, substance and adversarial (prompt-injection) testing produce a public Trust Score.
- Trust Score & evidence: https://superagentskill.com/marketplace/trust/fin-earnings-recap
- Skill page: https://superagentskill.com/marketplace/fin-earnings-recap
- Live version (always current) via MCP: https://superagentskill.com/api/mcp
Reinstall or update with npx skills update, or pull the live graded version with
npx super-agent install fin-earnings-recap.
Signals
- GitHub stars
- 308
- Forks
- 1
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
fin-earnings-recap- Source
- github.com/criptogus/agent-evolve-network