Daloopa Financial Analysis Toolkit

This is a financial analysis toolkit powered by Daloopa's institutional-grade financial data, designed for hedge fund analysts doing fundamental equity research.

Analyst Context

• Perspective: long/short equity, fundamental analysis
• Data source: Daloopa MCP server (SEC filings, earnings, financial statements)
• Market data: MCP-first (use whatever market data MCP the user has configured), fallback to infra/market_data.py
• Consensus estimates: optional (when available, adds beat/miss and forward context)
• All analysis should be thorough, data-driven, and cite sources
• Follow design-system.md for number formatting, analytical density, and styling

MCP Tool Workflow

Always follow this pattern when working with Daloopa data:

1. discover_companies — Look up company by ticker or name to get company_id
2. discover_company_series — Find available financial metrics and KPIs for the company
3. get_company_fundamentals — Pull actual data for specific series and periods
4. search_documents — Search SEC filings (10-K, 10-Q, 8-K) for qualitative information

Market Data

Market data uses whatever MCP the user has configured (preferred), falling back to infra/market_data.py if no market data MCP is available. See .claude/skills/data-access.md Section 2 for the full resolution order.

Fallback scripts (when no MCP provides market data):

• python infra/market_data.py quote TICKER — price, market cap, shares, beta
• python infra/market_data.py multiples TICKER — P/E, EV/EBITDA, P/S, P/B
• python infra/market_data.py history TICKER --period 2y — historical OHLCV
• python infra/market_data.py peers TICKER1 TICKER2 ... — side-by-side multiples
• python infra/market_data.py risk-free-rate — 10Y Treasury from FRED

Design System

All skills reference .claude/skills/design-system.md for consistent formatting:

• Number formatting ($X.Xbn, X.X%, X.Xx multiples, +/-Xbps)
• Three-layer analytical density (data point + context + implication)
• Table conventions (columns = periods, rows = metrics, growth sub-rows)
• Commentary blocks after every major table
• Color palette (navy #1B2A4A, steel blue #4A6FA5, gold #C5A55A)

Citation Format

Every financial figure must link back to its Daloopa source:

[$X.XX million](https://daloopa.com/src/{fundamental_id})

Example: Revenue grew to $75.2 billion

Table Format

Always use standard financial analysis layout:

• Columns = time periods (Q1 2024, Q2 2024, etc.)
• Rows = financial metrics (Revenue, Net Income, etc.)

Guidance vs Actuals Rules

• Quarterly guidance from Q(N) applies to Q(N+1) results
• Annual guidance from Q1/Q2/Q3 applies to current fiscal year
• Annual guidance from Q4 applies to NEXT fiscal year
• Never compare same-quarter guidance to same-quarter actual

Key Operating KPIs

When analyzing any company, always discover and include company-specific KPIs beyond standard financials (e.g., subscribers, ARR, GMV, same-store sales, DAU/MAU, ARPU, units, bookings, backlog).

Reports

All generated analysis is saved to the reports/ directory. Reports are gitignored so each analyst generates their own. Word documents, Excel models, PDFs, and decks are also saved there.

Available Commands

Building Block Skills (HTML reports)

• /setup — Walk through initial setup and authentication
• /earnings TICKER — Full earnings analysis with guidance tracking
• /earnings-prep TICKER — Pre-earnings preparation report for the night before a company reports
• /earnings-flash TICKER — Rapid first-read earnings flash
• /tearsheet TICKER — Quick one-page company overview
• /industry TICKER1 TICKER2 ... — Cross-company industry comparison
• /bull-bear TICKER — Bull/bear/base scenario framework
• /guidance-tracker TICKER — Track management guidance accuracy
• /inflection TICKER — Auto-detect biggest metric accelerations/decelerations
• /capital-allocation TICKER — Deep dive into buybacks, dividends, shareholder yield
• /dcf TICKER — Discounted cash flow valuation with sensitivity analysis
• /comps TICKER — Trading comparables with peer multiples and implied valuation
• /precedent-transactions TICKER — Precedent M&A transactions with deal multiples and implied valuation
• /comp-sheet TICKER — Multi-company industry comp sheet Excel model with deep KPIs
• /supply-chain TICKER — Interactive supply chain dashboard mapping suppliers, customers, and financial interdependencies
• /unit-economics TICKER — Bottoms-up unit economics decomposition
• /working-capital TICKER — Cash conversion cycle, earnings quality & working capital deep-dive

Investment Deliverables (.docx, .xlsx, .pdf)

• /research-note TICKER — Generate professional Word research note
• /build-model TICKER — Build multi-tab Excel financial model
• /initiate TICKER — Initiate coverage: generates both research note + Excel model
• /update TICKER — Refresh existing coverage with latest quarter's data
• /ib-deck TICKER — Generate institutional-grade pitch deck (HTML → PDF)

Infrastructure

• infra/market_data.py — Market data fallback via yfinance (price, multiples, history)
• infra/chart_generator.py — Professional chart generation (6 chart types: time-series, waterfall, football-field, pie, scenario-bar, dcf-sensitivity)
• infra/projection_engine.py — Forward financial projections
• infra/excel_builder.py — Multi-tab Excel model builder (single-company)
• infra/comp_builder.py — Multi-company comp sheet Excel builder (8 tabs)
• infra/docx_renderer.py — Word document renderer from templates
• infra/pdf_renderer.py — Markdown → styled HTML → PDF renderer
• infra/deck_renderer.py — HTML deck → PDF renderer
• infra/report_differ.py — Context JSON diff for update tracking
• templates/research_note.docx — Word template for research notes

Plugin

The building block skills are also available as standalone plugins in two sibling repos: ../daloopa-plugin-claude/ (Claude Code plugin) and ../daloopa-plugin-codex/ (Codex plugin, derived from the Claude version — no argument-hint/$ARGUMENTS, plus per-skill agents/openai.yaml). The plugins use MCP + generic market data language (no Python infrastructure required). Use scripts/sync_plugin.sh to sync shared skill files to both plugin repos. Note: each plugin repo maintains its own simplified skills/data-access.md — shared policy changes (e.g., Source Quality rules) must be applied to those copies manually.

API Documentation

The daloopa-docs MCP server provides direct access to Daloopa's knowledgebase for API usage questions, data coverage, and platform features. A local copy of the docs is also in daloopa_docs/. See also: https://docs.daloopa.com