HHFinAi

Earnings Analysis — Development skill for Claude Code

Development community

quick earnings analysis with consensus Wall Street forecast, with past guidance, with peer industry trend.

How to install Earnings Analysis

This entry records only its repository, not the path inside it, so there is no exact command to give. Open HHFinAi/earnings-analysis and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Earnings Analysis does

quick earnings analysis with consensus Wall Street forecast, with past guidance, with peer industry trend.

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README

earnings-analysis

**Responsible AI:** Analyst-controlled research; verify evidence, disclose AI assistance and protect confidential information. [Policy and project-specific checks](RESPONSIBLE_AI.md). quick earnings analysis with consensus Wall Street forecast, with past guidance, with peer industry trend. An Agent Skill for institutional-quality earnings analysis from 10-Q/10-K filings, earnings releases, and call transcripts. Built for buyside-style post-print review that goes beyond beat/miss reporting to diagnose why results deviated, what changed in the forward thesis, and what action follows. What it does This skill encodes a structured editorial process distilled from buyside equity research practice. When loaded into an AI tool, it processes raw earnings materials through a four-layer framework:

Parse. Extracts structured financial KPIs, segment data, guidance, non-GAAP reconciliations, balance sheet and cash flow items, and sector-specific metrics from filings, releases, and transcripts. Compare. Benchmarks results sequentially (QoQ), year-over-year (YoY), against consensus estimates, and against sector peers — flagging surprises and trend breaks. Diagnose. Attributes deviations to underlying drivers (volume vs price, mix, FX, one-offs, structural shifts), assesses earnings quality, scores management tone from call transcripts, and detects negative triggers. Translate to action. Converts the analysis into a forward investment view: what's mispriced, what's de-risked, what to watch, and what to do.

The skill ships with a scoring engine, a flag library for earnings quality red flags, sector-specific KPI extensions, and a process discipline checklist to keep analysis honest under time pressure. What it produces The skill outputs four deliverables, scaled to the user's request:

One-page earnings sheet. Headline numbers, beat/miss table, segment snapshot, guidance delta, and the 4-layer summary — designed to fit a single screen for morning meetings. Ful