adityahimaone/hermes-agent-rtk-caveman/financial-analysis-automation

Financial Analysis Automation Skill

Use this skill to create automated financial analysis workflows that:

1. Scan multiple sources for investment opportunities
2. Run on a schedule (via cron jobs)
3. Save formatted results to Obsidian vault
4. Can be monitored and tracked

When to Use

• When you want to create custom stock/scanning analysis
• When you need analysis to run automatically on a schedule
• When you want results saved to your Obsidian vault for review
• When you need to track multiple financial data sources
• When you want to combine web crawling with sentiment analysis

Core Components

1. Analysis Skill Creation

Create a custom skill that includes:

• Data Sources: Define where to get information (websites, APIs, social media)
• Analysis Logic: Define what to look for (volume spikes, sentiment, patterns)
• Output Format: Define how results should be presented
• Error Handling: Define what to do when sources fail

2. Automation Setup

Set up scheduled execution using:

• Cron Jobs: Schedule the skill to run at specific times
• Skill Chaining: Combine multiple skills (e.g., analysis + note saving)
• Time Filtering: Ensure only recent data is analyzed
• Source Validation: Validate data quality and freshness

3. Result Storage

Configure automatic saving to:

• Obsidian Vault: Save results as formatted notes
• Proper Frontmatter: Include metadata for filtering and linking
• Consistent Naming: Use date-based filenames for easy sorting
• Tagging System: Add relevant tags for discovery

Workflow Steps

Step 1: Define Analysis Requirements

• What financial instruments to analyze (stocks, crypto, etc.)
• What data sources to use (financial sites, social media, news)
• What specific metrics or patterns to look for
• What time sensitivity is required (real-time, daily, weekly)

Step 2: Create the Analysis Skill

Create a custom Hermes skill that:

• Uses appropriate data extraction methods (firecrawl, web_search, etc.)
• Applies your analysis logic and filters
• Formats output in a consistent, readable way
• Includes risk disclaimers and limitations

Step 3: Set Up Automation

Configure a cron job that:

• Runs your analysis skill on the desired schedule
• Chains with appropriate output skills (obi-notes, etc.)
• Includes proper error handling and logging
• Runs during appropriate market hours

Step 4: Configure Output Storage

Set up the result saving to:

• Create appropriate folder structure in Obsidian
• Generate properly formatted markdown with frontmatter
• Include metadata about the analysis (time, sources, etc.)
• Add relevant tags for easy discovery and filtering

Step 5: Monitor and Maintain

• Check that the cron job runs successfully
• Verify output is correctly formatted and saved
• Update analysis logic as market conditions change
• Refresh API keys and credentials as needed

Example: Market Alpha Scout

The market_alpha_scout skill demonstrates this workflow:

• Analysis Skill: market_alpha_scout (research category)
• Data Sources:
• Stockbro.id (firecrawl crawl with Google Workspace auth)
• Financial news sites (Google search: detik, kontan, bisnis)
• Social sentiment (Google search: X/Twitter content like @happenfed)
• Schedule: Weekdays at 08:15 WIB (before market open)
• Output: Saved to Notes/Stockpick/Stockpick - [Tanggal].md
• Features:
• Volume filtering (V > V_avg20)
• Time sensitivity (last 12 hours)
• Multi-source validation
• High conviction setup identification
• Sector diversification

Integration Notes

This approach integrates multiple Hermes skills:

• crawl4ai (primary): Self-hosted web scraping via Crawl4AI (free, unlimited)
• firecrawl (fallback): For web crawling when Crawl4AI unavailable
• web_search: DuckDuckGo search via Crawl4AI wrapper
• obi-notes: For saving results to Obsidian vault
• cronjob: For scheduling automated execution
• skill-documentation: For maintaining skill documentation

Prerequisites

• Crawl4AI: installed in Hermes venv (pip install crawl4ai + playwright install chromium)
• Python 3.11 (Hermes venv): ~/.hermes/hermes-agent/venv/bin/python3.11
• Firecrawl (optional fallback): API key for when Crawl4AI fails
• Access to financial data sources
• Obsidian vault configured for saving analysis results

Customization Options

This workflow can be adapted for:

• Different financial instruments (crypto, forex, commodities)
• Different analysis techniques (technical, fundamental, sentiment)
• Different schedules (intraday, daily, weekly, monthly)
• Different output formats (alerts, reports, watchlists)
• Different notification methods (email, messaging, dashboard)

Verification Checklist

After setting up financial analysis automation:

• [ ] Analysis skill creates and executes without errors
• [ ] Data is correctly extracted from all sources
• [ ] Analysis logic is applied correctly (filters, calculations)
• [ ] Output is properly formatted and readable
• [ ] Results are saved to the correct Obsidian location
• [ ] Frontmatter and metadata are correctly included
• [ ] Cron job runs on the scheduled time
• [ ] Results are generated and saved as expected
• [ ] Error handling works appropriately when sources fail