원클릭으로
원클릭으로
| name | setup |
| description | Walk through initial setup and authentication for this Daloopa starter kit |
Walk the user through setting up this Daloopa starter kit step by step. Be conversational and helpful.
Confirm Claude Code is running (if the user is seeing this, it is — tell them they're good).
Check if required packages are installed. Offer to install them:
pip3 install -r requirements.txt
This installs: requests, beautifulsoup4, html2text, yfinance, openpyxl, python-docx, docxtpl, matplotlib, fredapi.
These are needed for market data, chart generation, Excel model building, and Word document rendering.
Ask the user which authentication method they'd like to use:
Option A: OAuth (Recommended)
.mcp.json is already configured for OAuthOption B: API Key
.env with their key: DALOOPA_API_KEY=<their_key>daloopa entry in .mcp.json to include the API key header (keep the daloopa-docs entry as-is):{
"mcpServers": {
"daloopa": {
"type": "http",
"url": "https://mcp.daloopa.com/server/mcp",
"headers": {
"x-api-key": "${DALOOPA_API_KEY}"
}
},
"daloopa-docs": {
"type": "http",
"url": "https://docs.daloopa.com/mcp"
}
}
}
Ask if they want to configure optional API keys for enhanced functionality:
FRED API Key (recommended for DCF/valuation work):
.env: FRED_API_KEY=<their_key>This project connects to two Daloopa MCP servers:
mcp.daloopa.com/server/mcp) — Financial data (fundamentals, KPIs, SEC filings)docs.daloopa.com/mcp) — Daloopa knowledgebase (API docs, how-tos, usage help)Run a quick test by calling discover_companies with a well-known ticker like "AAPL" to confirm the data MCP server is connected and responding. Show the user the result.
If the user has a market data MCP configured (e.g., a financial data provider with stock quote tools), test it by looking up AAPL.
If no market data MCP is available, fall back to the infra script: python infra/market_data.py quote AAPL
This should return current price, market cap, etc.
Run: python scripts/create_template.py
This creates the research note template at templates/research_note.docx.
Tell the user about the available slash commands:
Building Block Skills (markdown reports):
/earnings-review TICKER — Full earnings analysis with guidance tracking/tearsheet TICKER — Quick one-page company overview/industry TICKER1 TICKER2 ... — Cross-company comparison/bull-bear TICKER — Bull/bear/base scenario framework/guidance-tracker TICKER — Track management guidance accuracy/inflection TICKER — Auto-detect metric accelerations/decelerations/capital-allocation TICKER — Buybacks, dividends, shareholder yield/dcf TICKER — DCF valuation with sensitivity analysis/comps TICKER — Trading comparables with peer multiplesInvestment Deliverables (.docx, .xlsx, .pdf):
/research-note TICKER — Professional Word research note/build-model TICKER — Multi-tab Excel financial model/initiate TICKER — Both research note + Excel model (initiating coverage)/update TICKER — Refresh existing coverage with latest data/ib-deck TICKER — Institutional-grade pitch deck (HTML → PDF)All output is saved to the reports/ directory.
Suggest they try /tearsheet AAPL as a quick first test to see everything working end-to-end.
Build an industry comp sheet Excel model with deep operational KPIs
Trading comparables analysis with peer multiples and implied valuation
Rapid first-read earnings flash for a given company
Pre-earnings preparation report for the night before a company reports
Full earnings analysis with guidance tracking for a given company
Bull/bear/base case scenario framework for a given company