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Earnings Preview

skill-w95-awesome-claude-corporate-skills-earnings-preview · by w95

A Claude skill from w95/awesome-claude-corporate-skills.

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Install

$ agentstack add skill-w95-awesome-claude-corporate-skills-earnings-preview

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Earnings Preview

description: Build pre-earnings analysis with estimate models, scenario frameworks, and key metrics to watch. Use before a company reports quarterly earnings to prepare positioning notes, set up bull/bear scenarios, and identify what will move the stock. Triggers on "earnings preview", "what to watch for [company] earnings", "pre-earnings", "earnings setup", or "preview Q[X] for [company]".

Workflow

Step 1: Gather Context

  • Identify the company and reporting quarter
  • Pull consensus estimates via web search (revenue, EPS, key segment metrics)
  • Find the earnings date and time (pre-market vs. after-hours)
  • Review the company's prior quarter earnings call for any guidance or commentary

Step 2: Key Metrics Framework

Build a "what to watch" framework specific to the company:

Financial Metrics:

  • Revenue vs. consensus (total and by segment)
  • EPS vs. consensus
  • Margins (gross, operating, net) — expanding or contracting?
  • Free cash flow
  • Forward guidance vs. consensus

Operational Metrics (sector-specific):

  • Tech/SaaS: ARR, net retention, RPO, customer count
  • Retail: Same-store sales, traffic, basket size
  • Industrials: Backlog, book-to-bill, price vs. volume
  • Financials: NIM, credit quality, loan growth, fee income
  • Healthcare: Scripts, patient volumes, pipeline updates

Step 3: Scenario Analysis

Build 3 scenarios with stock price implications:

| Scenario | Revenue | EPS | Key Driver | Stock Reaction | |----------|---------|-----|------------|----------------| | Bull | | | | | | Base | | | | | | Bear | | | | |

For each scenario:

  • What would need to happen operationally
  • What management commentary would signal this
  • Historical context — how has the stock moved on similar prints?

Step 4: Catalyst Checklist

Identify the 3-5 things that will determine the stock's reaction:

  1. [Metric] vs. [consensus/whisper number] — why it matters
  2. [Guidance item] — what the buy-side expects to hear
  3. [Narrative shift] — any strategic changes, M&A, restructuring

Step 5: Output

One-page earnings preview with:

  • Company, quarter, earnings date
  • Consensus estimates table
  • Key metrics to watch (ranked by importance)
  • Bull/base/bear scenario table
  • Catalyst checklist
  • Trading setup: recent stock performance, implied move from options

Important Notes

  • Consensus estimates change — always note the source and date of estimates
  • "Whisper numbers" from buy-side surveys are often more relevant than published consensus
  • Historical earnings reactions help calibrate expectations (search for "[company] earnings reaction history")
  • Options-implied move tells you what the market expects — compare to your scenarios

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.