> For the complete documentation index, see [llms.txt](https://docs.orbitfin.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.orbitfin.ai/orbit-api-reference/mcp/2.-orbit-public-company-research-mcp/2.8.-best-practices.md).

# 2.8. Best Practices

#### Query Optimization

1. **Be Specific**: Include specific metrics and timeframes
   * Good: "Compare Apple and Microsoft's operating margins for Q3 2024"
   * Avoid: "How are Apple and Microsoft doing?"
2. **Use Identifiers**: Include tickers when possible
   * Good: "Analyze AAPL's capital allocation strategy"
   * Okay: "Analyze Apple's capital allocation strategy"
3. **Optimal Company Count**: 2-3 companies for best results
   * Detailed analysis possible
   * Meaningful comparisons
   * Faster processing
4. **Specify Document Types**: When relevant
   * "According to Tesla's latest 10-Q..."
   * "Based on proxy statements..."

#### Response Interpretation

1. **Check Citations**: Always review source documents cited
2. **Understand Timing**: Note filing dates for context
3. **Consider Limitations**: 12-month data window constraint
4. **Cross-Reference**: Validate critical data points

#### Workflow Efficiency

1. **Start Narrow**: Begin with focused queries, then expand
2. **Use Sub-Queries**: Break complex questions into parts
3. **Save Key Findings**: Document important insights
4. **Build Knowledge**: Each query informs the next

#### Common Use Cases

1. **Earnings Analysis**: Pre/post earnings call research
2. **Peer Benchmarking**: Competitive positioning
3. **Risk Assessment**: Systematic risk factor analysis
4. **Trend Identification**: Multi-period comparisons