agentleFS
daloopadaloopa/investing/.claude/skills/setup/SKILL.md

setup

Skill489 starsChanged 3 months agoApache-2.0View on GitHub

Walk through initial setup and authentication for this Daloopa starter kit

  • Reads credentials

We split this skill into the rules it gives an agent

12 rules. 0 are common, 6 are distinctive, and 6 are very specific to this project.

  • 0

    Common

    Most of the 168 edited versions we read keep these.

  • 6

    Distinctive

    This author's own choices. Worth a look.

  • 6

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Check if required packages are installed.

    line 12
  2. Distinctive:

    Ask the user which authentication method they'd like to use:

    line 21
  3. Distinctive:

    No additional configuration needed

    line 26
  4. Distinctive:

    Ask the user for their Daloopa API key

    line 30
  5. Very specific:

    Create/update .env with their key: DALOOPA_API_KEY=<their_key>

    line 31
  6. Very specific:

    Update the daloopa entry in .mcp.json to include the API key header (keep the daloopa-docs entry as-is):

    line 32
  7. Distinctive:

    Ask if they want to configure optional API keys for enhanced functionality:

    line 53
  8. Very specific:

    Add to .env: FRED_API_KEY=<their_key>

    line 59
  9. Very specific:

    Run a quick test by calling discover_companies with a well-known ticker like "AAPL" to confirm the data MCP server is connected and …

    line 67
  10. Distinctive:

    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.

    line 70
  11. Very specific:

    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, …

    line 72
  12. Very specific:

    All output is saved to the reports/ directory.

    line 100

“Common” is measured: kept by at least 6 in 10 of the 168 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Walk the user through setting up this Daloopa starter kit step by step. Be conversational and helpful.

Step 1: Verify Claude Code

Confirm Claude Code is running (if the user is seeing this, it is — tell them they're good).

Step 2: Install Python Dependencies

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.

Step 3: Daloopa Authentication

Ask the user which authentication method they'd like to use:

Option A: OAuth (Recommended)

  • The .mcp.json is already configured for OAuth
  • On the next MCP tool call, a browser window will open for Daloopa login
  • No additional configuration needed
  • Just make sure they have a Daloopa account at daloopa.com

Option B: API Key

  • Ask the user for their Daloopa API key
  • Create/update .env with their key: DALOOPA_API_KEY=<their_key>
  • Update the 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"
    }
  }
}
  • Tell them they'll need to restart Claude Code for the change to take effect

Step 4: Optional API Keys

Ask if they want to configure optional API keys for enhanced functionality:

FRED API Key (recommended for DCF/valuation work):

Step 5: Verify MCP Connection

This project connects to two Daloopa MCP servers:

  • daloopa (mcp.daloopa.com/server/mcp) — Financial data (fundamentals, KPIs, SEC filings)
  • daloopa-docs (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.

Step 6: Verify Market Data

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.

Step 7: Create Word Template

Run: python scripts/create_template.py This creates the research note template at templates/research_note.docx.

Step 8: Quick Tour

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 multiples

Investment 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.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

Reviews can't be read right now.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.