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earnings-preview

Generate pre-earnings preview reports from local CSV financial data.

8|12|Updated Sep 19, 2025
Search Tags:#portfolio management#financial analysis#kpi dashboard#earnings preview#consensus estimates#public equity#sell-side research
One-click install
npx skills add https://github.com/xpert-ai/xpert-plugins --skill earnings-preview-xpert-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: earnings-preview
Source: https://github.com/xpert-ai/xpert-plugins/tree/main/community/roles/financial-markets/skills/earnings-preview
Command: npx skills add https://github.com/xpert-ai/xpert-plugins --skill earnings-preview-xpert-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, pyyaml, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Public equity analysts and portfolio managers waste hours manually compiling fragmented earnings data, consensus estimates, whisper numbers, and peer context into coherent pre-earnings previews. This Skill automates the end-to-end workflow, producing decision-grade reports with expectation bars, KPI dashboards, scenario maps, and call questions so you can focus on investment judgment rather than document assembly.

Core Features & Use Cases

  • Full Preview Reports: Generates polished standalone HTML pre-earnings reports with executive summary, expectation bar, guidance credibility, bull/base/bear scenarios, and must-answer call questions.
  • Deterministic Export Pack: Produces validated XLSX workbooks, CSV sidecars, QA reports, and run manifests from local CSV inputs for reproducible analyst workflows.
  • Sector-Aware KPIs: Automatically selects relevant KPI packs for SaaS, semiconductors, consumer retail, banks, energy, and other sectors with proper margin and metric framing.

Quick Start

Use the earnings-preview skill to generate a full pre-earnings preview report for your target company and quarter, including the expectation bar, KPI dashboard, scenarios, and call questions.

Frequently Asked Questions about earnings-preview

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

FAQPage Schema
How do I generate a pre-earnings preview report from consensus estimates and financial KPIs?▼

Generate a pre-earnings preview report by loading local CSV inputs like consensus estimates, reported financials, and KPI timeseries to synthesize expectation bars, scenario maps, and call questions into a structured HTML output.

Can I use this to prepare earnings call questions for sell-side research workflows?▼

Yes, this earnings preview workflow produces must-answer call questions, guidance credibility checks, and bull/base/bear scenarios specifically tailored for sell-side research, long-only PM, and hedge fund diligence.

What data inputs do I need to build an earnings preview report with scenario maps?▼

You need local CSV files including company master, fiscal period index, reported financials, KPI timeseries, and consensus estimates, with optional guidance history, whisper estimates, and options snapshot inputs for deeper scenario mapping.

Does the earnings preview workflow support sector-specific KPI dashboards for SaaS and semiconductor companies?▼

Yes, the earnings preview workflow automatically selects sector-aware KPI packs for SaaS, semiconductors, consumer retail, banks, and energy, applying proper margin and metric framing to the generated KPI dashboards.

What is the best way to export reproducible pre-earnings analyst workbooks and QA reports?▼

Export reproducible analyst workflows using the deterministic export pack feature, which produces validated XLSX workbooks, CSV sidecars, QA reports, and run manifests directly from your local CSV financial inputs.

How do whisper numbers and market context factor into pre-earnings preview generation?▼

Whisper estimates and market context are synthesized alongside consensus estimates and guidance history to establish expectation bars and EPS-quality watches, enhancing the decision-grade quality of the pre-earnings preview output.

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