fsi-er-earnings-preview
Build pre-earnings analysis with estimate models, scenario frameworks, and key metrics to watch.
Skill by d-wwei
Chalk Labs
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/d-wwei-fsi-er-earnings-preview
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: productivity, finance
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/fsi-er-earnings-preview
What's inside
- Skill name
fsi-er-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]".
- License
- Apache-2.0
- Instructions
- 71 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Earnings Preview ## 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
From d-wwei/openclaw-financial-services, Apache-2.0.
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Signals
- Stars
- 17
- Forks
- 4
- Open issues
- 0
- Last commit (this folder)
- Feb 25, 2026 (8 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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fsi-fa-check-deck
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Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
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fsi-er-earnings-preview skill. Agent Mart. https://agentmart.dev/skills/d-wwei-fsi-er-earnings-preview (last updated 2026-10-24)