financereport
Generates detailed financial analysis PDFs for stocks and ETFs, integrating sentiment data and market metrics.
Install
mkdir -p .claude/skills/financereport && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/1418" && unzip -o skill.zip -d .claude/skills/financereport && rm skill.zipInstalls to .claude/skills/financereport
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Generate institutional-quality PDF analysis reports for stocks and ETFs. USE WHEN user mentions generate report, create pdf, stock analysis, ticker report, watchlist analysis, OR regenerate reports. Includes VGT-style headers, embedded charts, portfolio sizing, and Perplexity sentiment integration.Key capabilities
- →Runs quantitative risk metrics and momentum analysis
- →Fetches sentiment data via Perplexity MCP
- →Generates standardized 8-10 page PDF research documents
- →Calculates portfolio sizing and strategy recommendations
How it works
It orchestrates a multi-step workflow involving quantitative analysis, sentiment fetching, and PDF generation using VGT-style headers.
Inputs & outputs
When to use financereport
- →Generate stock performance reports
- →Create watchlist analysis PDFs
- →Conduct thorough research on assets
About this skill
FinanceReport
Generate comprehensive 8-10 page PDF investment analysis reports with Finance Guru branding.
Workflow Routing
When executing a workflow, output this notification directly:
Running the **WorkflowName** workflow from the **FinanceReport** skill...
| Workflow | Trigger | File |
|---|---|---|
| GenerateSingleReport | "generate report for TSLA", "create PDF" | workflows/GenerateSingleReport.md |
| RegenerateBatch | "regenerate batch", "redo all reports" | workflows/RegenerateBatch.md |
| FullResearchWorkflow | "full analysis", "thorough research" | workflows/FullResearchWorkflow.md |
Examples
Example 1: Generate single ticker report
User: "Generate a report for NVDA"
-> Invokes GenerateSingleReport workflow
-> Runs quant tools (risk_metrics, momentum, volatility)
-> Fetches sentiment via Perplexity MCP
-> Builds 8-10 page PDF with VGT-style header
-> Saves to fin-guru-private/fin-guru/analysis/reports/NVDA-analysis-2025-12-18.pdf
Example 2: Regenerate all watchlist reports
User: "Regenerate batch 1 reports"
-> Invokes RegenerateBatch workflow
-> Launches 8 subagents in parallel
-> Each runs FullResearchWorkflow
-> Replaces existing PDFs with improved versions
Example 3: Deep research with full workflow
User: "Do a full analysis on AMZN for the 2026 watchlist"
-> Invokes FullResearchWorkflow
-> Phase 1: Market research (Perplexity/Exa for catalysts, risks)
-> Phase 2: Quant analysis (252-day risk metrics, 90-day momentum)
-> Phase 3: Strategy recommendation (buy/hold/sell, position sizing)
-> Phase 4: Generate comprehensive PDF report
Report Structure (8-10 Pages)
Cover Page (VGT-Style Header) - UNIFORM STANDARD
CRITICAL: Every report MUST follow this EXACT format:
┌─────────────────────────────────────────────────────────────┐
│ FINANCE GURU™ │
│ Family Office Investment Analysis │
│ ───────────────────────────────────────────────────────── │
│ │
│ TICKER - Full Company/Fund Name │
│ 2026 Watchlist Analysis & Investment Report │
│ │
├─────────────────────────────────────────────────────────────┤
│ Report Date: December 18, 2025 │
│ Analyst Team: Finance Guru Multi-Agent System │
│ • Market Researcher (Dr. Aleksandr Petrov)│
│ • Quant Analyst │
│ • Strategy Advisor │
│ Current Price: $XXX.XX │
│ YTD Performance: +XX.XX% │
│ Expense Ratio: 0.XX% (ETFs only) │
└─────────────────────────────────────────────────────────────┘
UNIFORMITY RULES:
- Analyst team names MUST be listed on EVERY report
- "Finance Guru Multi-Agent System" header REQUIRED
- Individual analyst names with personas (e.g., Dr. Aleksandr Petrov)
- Same format, same structure, every single time
Executive Summary
- Investment thesis (200+ words)
- Key findings with bold labels
- Final verdict box (rating, conviction, risk level)
Quantitative Analysis
- Risk metrics table (VaR, Sharpe, Beta, Alpha)
- Momentum indicators (RSI, MACD, Stochastic)
- Volatility assessment (ATR, Bollinger regime)
- Embedded charts where applicable
TABLE FORMATTING - CRITICAL:
- All table cells use Paragraph objects (text wraps, never overflows)
- Column widths explicitly set to fit within 7.5" content area
- Header row: Navy background, white text, bold
- Data rows: Alternating white/light gray backgrounds
Market Research
- Company overview and positioning
- 2026 catalysts and risks
- Analyst ratings and sentiment
- Perplexity MCP integration
Portfolio Sizing (NEW)
Shows BOTH percentage AND dollar amount:
Recommended Allocation: 2-3%
For $250,000 portfolio:
- Dollar amount: $5,000 - $7,500
- Share count: ~25-38 shares at $200
Strategy Recommendations
- Entry strategy with price targets
- Risk management (stop-loss levels)
- Position management approach
Sources & Disclaimer - UNIFORM STANDARD
CRITICAL: Every report MUST end with this EXACT format:
─────────────────────────────────────────────────────────────
DISCLAIMER: This analysis is provided for educational and
informational purposes only. [full disclaimer text]
Powered by Finance Guru™
Report Date: December 18, 2025
─────────────────────────────────────────────────────────────
"Powered by Finance Guru™" is REQUIRED on every report.
Tool Usage
ChartKit.py
uv run python .claude/skills/FinanceReport/tools/ChartKit.py \
--ticker TSLA \
--chart-type line \
--data-source cli
ReportGenerator.py
uv run python .claude/skills/FinanceReport/tools/ReportGenerator.py \
--ticker TSLA \
--portfolio-value 250000 \
--output-dir fin-guru-private/fin-guru/analysis/reports/
Integration Points
Perplexity MCP (Sentiment & Research)
# Search for market sentiment
mcp__perplexity__search(query=f"{ticker} stock analysis 2025 catalysts risks")
# Deep reasoning for thesis
mcp__perplexity__reason(query=f"Analyze {ticker} investment thesis for 2026")
Existing Finance Guru CLI Tools
src/analysis/risk_metrics_cli.py- VaR, CVaR, Sharpe, Sortino, Beta, Alphasrc/utils/momentum_cli.py- RSI, MACD, Stochastic, Williams %Rsrc/utils/volatility_cli.py- ATR, Bollinger Bands, Keltner Channelssrc/analysis/correlation_cli.py- Portfolio correlation matrix
User Profile
Reads portfolio value from fin-guru/data/user-profile.yaml for sizing:
investment_portfolio.total_value= Current portfolio value- Calculates exact dollar amounts for recommendations
Reference Files
- StyleGuide.md - Brand colors, typography, table styling
- VisGuide.md - Chart selection dictionary, labeling standards
Skill Type: Domain Enforcement: Suggest Priority: High Line Count: < 200 lines
When not to use it
- →When the user needs live trading execution rather than reports
- →For assets where public market data is unavailable
Prerequisites
Limitations
- →Report generation is computationally intensive
- →Depends on external sentiment analysis service availability
How it compares
It automates the aggregation of quantitative data and sentiment into a standardized institutional format, rather than just returning raw data.
Compared to similar skills
financereport side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| financereport (this skill) | 6 | 5mo | Review | Intermediate |
| quant-analyst | 103 | 2mo | No flags | Advanced |
| stock-analyzer | 71 | 2mo | Review | Beginner |
| creating-financial-models | 36 | 8mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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