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earnings-deep-dive

Analyzes public company earnings releases and SEC filings into investment research reports.

8|12|Updated Sep 19, 2025
Search Tags:#earnings#financial-analysis#investment-research#transcript-analysis#sec-filings#post-earnings#public-equity
One-click install
npx skills add https://github.com/xpert-ai/xpert-plugins --skill earnings-deep-dive-xpert-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: earnings-deep-dive
Source: https://github.com/xpert-ai/xpert-plugins/tree/main/community/roles/financial-markets/skills/earnings-deep-dive
Command: npx skills add https://github.com/xpert-ai/xpert-plugins --skill earnings-deep-dive-xpert-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, openpyxl, python-dateutil, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Public equity analysts and portfolio managers struggle to turn raw earnings releases, filings, transcripts, and estimates into decision-grade post-print analysis quickly and consistently. This Skill automates the end-to-end workflow so you can focus on investment judgment instead of formatting and source tracking.

Core Features & Use Cases

  • Full Deep Dive Generation: Produces polished standalone HTML post-earnings reports with beat/miss, EPS quality screens, transcript Q&A, debate maps, guidance deltas, and model impact.
  • Deterministic File Mode: Validates inputs, runs shipped scripts, and applies model updates via driver registries when you supply plan.json or normalized CSVs.
  • Standardized Dashboard Handoff: Maps analysis into a structured payload for the dashboard-builder when you need a reusable PM cockpit or tabbed dashboard.

Quick Start

Use the earnings-deep-dive skill to analyze the latest quarterly results for ticker AAPL and produce a full standalone HTML deep dive report.

Frequently Asked Questions about earnings-deep-dive

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate post-earnings financial analysis for public equities?▼

Post-earnings financial analysis is automated by processing earnings releases, SEC filings, and transcripts to generate decision-grade investment research. This Skill produces standalone HTML deep dive reports with beat/miss screens and guidance deltas.

Can I update Excel financial models automatically after an earnings release?▼

Excel financial models can be updated automatically using driver registries during post-earnings analysis. You need to supply optional Excel model registries along with normalized CSVs or plan.json for deterministic file mode execution.

What is the best way to extract Q&A insights from earnings call transcripts?▼

Earnings call transcript Q&A insights are extracted by analyzing source-tagged inputs to map debates and produce model impact assessments. This process standardizes transcript analysis into a structured dashboard payload for portfolio managers.

Does earnings-deep-dive require source-tagged inputs for deterministic mode?▼

Earnings-deep-dive deterministic mode requires source-tagged inputs, normalized CSVs, or a plan.json file to validate data and run shipped scripts. Optional Excel model registries are supported for workbook updates.

How do I create a standardized dashboard payload from SEC filings and consensus estimates?▼

Standardized dashboard payloads from SEC filings and consensus estimates are created by mapping post-earnings analysis into a structured format. This output feeds directly into a dashboard-builder for a reusable PM cockpit.

What limitations exist when using plan.json for post-earnings deep dives?▼

Plan.json post-earnings deep dives require normalized CSVs or source-tagged inputs to function deterministically. Without validated inputs, the Skill cannot execute shipped scripts or apply audit-ready model updates.

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