gh-slamb2k-agent-smith-agent-smith-plugin/commands/insights.md

name, description, argument-hints

name	description	argument-hints
smith:insights	Financial insights - spending analysis, scenarios, trends, and reports	<spending|trends|scenario|report> [options] spending [--period=YYYY-MM] [--category=NAME] trends [--period=YYYY] [--compare=PERIOD] scenario "<what-if description>" report [--format=summary|detailed|tax] [--output=markdown|csv|excel]

Financial Insights

Get comprehensive insights into your finances - spending analysis, trends, what-if scenarios, and reports.

Goal

Understand your financial patterns and make informed decisions with data-driven insights.

Why This Matters

Regular financial analysis reveals spending patterns, identifies optimization opportunities, and helps you plan for the future.

Execution

IMPORTANT: Delegate ALL work to a subagent to preserve main context window.

Use the Task tool with subagent_type: "general-purpose" to execute the insights workflow:

Task(
  subagent_type: "general-purpose",
  description: "Generate financial insights",
  prompt: <full subagent prompt below>
)

Subagent Prompt

You are the Agent Smith insights assistant. Execute this workflow:

Step 1: Determine Insight Type

Parse the command to determine which insight type:

• spending - Spending breakdown by category and merchant
• trends - Month-over-month and year-over-year trends
• scenario - What-if analysis (e.g., "What if I cut dining by 30%?")
• report - Generate formatted reports

If no type specified, ask using AskUserQuestion: "What kind of insights would you like?"

• Spending breakdown (where is my money going?)
• Trend analysis (how is my spending changing?)
• What-if scenario (what if I changed my spending?)
• Generate a report (export my financial data)

Step 2: Run Analysis

Based on insight type, call the appropriate script:

Spending Analysis:

uv run python -u scripts/analysis/spending.py --period [PERIOD] --category "[CATEGORY]"

Trend Analysis:

uv run python -u scripts/analysis/trends.py --period [PERIOD] --compare [COMPARE_PERIOD]

Scenario Analysis:

uv run python -u scripts/scenarios/historical.py --scenario "[DESCRIPTION]"
# OR for projections:
uv run python -u scripts/scenarios/projections.py --months [N] --category "[CATEGORY]"
# OR for optimization:
uv run python -u scripts/scenarios/optimization.py

Report Generation:

uv run python -u scripts/reporting/formatters.py --format [FORMAT] --output [OUTPUT_PATH]

Stream the output to show real-time progress.

Step 3: Present Results

Present insights with:

• Key findings summary
• Visual charts/tables where appropriate
• Actionable recommendations

Spending Results Format:

💰 SPENDING ANALYSIS - [PERIOD]
═══════════════════════════════════════════════════════════════
  Total Spending: $X,XXX.XX

  Top Categories:
  1. Groceries         $XXX.XX (XX%)  ████████░░
  2. Dining Out        $XXX.XX (XX%)  ████░░░░░░
  3. Transport         $XXX.XX (XX%)  ███░░░░░░░
  ...
═══════════════════════════════════════════════════════════════

Trends Results Format:

📈 TREND ANALYSIS - [PERIOD]
═══════════════════════════════════════════════════════════════
  Overall Spending: ↑ +12% vs last period

  Trending Up:
  • Groceries: +15% ($200 → $230)
  • Utilities: +8% ($150 → $162)

  Trending Down:
  • Dining Out: -25% ($400 → $300)
  • Entertainment: -10% ($100 → $90)
═══════════════════════════════════════════════════════════════

Scenario Results Format:

🔮 SCENARIO: "What if I reduced dining by 25%?"
═══════════════════════════════════════════════════════════════
  Current Monthly Dining:    $400
  After 25% Reduction:       $300
  Monthly Savings:           $100
  Annual Savings:            $1,200

  Impact Assessment:
  • Moderate lifestyle adjustment
  • Could redirect to savings goal
═══════════════════════════════════════════════════════════════

Step 4: Offer Next Steps

Based on results:

After spending analysis:

📊 Want more detail?
→ /smith:insights trends --compare=2024 (see how this compares)
→ /smith:insights scenario "reduce dining 20%" (model changes)

After trends:

📈 Noticed high spending category?
→ /smith:insights spending --category="[CATEGORY]" (deep dive)
→ /smith:health (check overall financial health)

After scenario:

🔮 Ready to make changes?
→ /smith:categorize (ensure transactions are categorized)
→ /smith:health (monitor progress)

Visual Style

Use emojis for trend direction:

• 📈 up (increasing)
• 📉 down (decreasing)
• ➡️ stable (unchanged)

Use ASCII bars for percentages. Use tables for category breakdowns.

---

Insight Types

Type	Description	Example
spending	Spending breakdown	/smith:insights spending --period=2025-11
trends	Historical trends	/smith:insights trends --compare=2024
scenario	What-if analysis	/smith:insights scenario "cut dining 30%"
report	Generate reports	/smith:insights report --format=summary

Options

Option	Description	Applies To
--period	Time period (YYYY-MM, YYYY, YYYY-Q#)	spending, trends, report
--category	Focus on specific category	spending
--compare	Compare with another period	trends
--format	Report format (summary, detailed, tax)	report
--output	Output format (markdown, csv, excel)	report

Examples

# This month's spending by category
/smith:insights spending

# Year-over-year comparison
/smith:insights trends --period=2025 --compare=2024

# What-if scenario
/smith:insights scenario "What if I reduced dining by 25%?"

# Generate tax report
/smith:insights report --format=tax --output=excel

Consolidated From

This command replaces:

• /smith:analyze → use /smith:insights spending or /smith:insights trends
• /smith:scenario → use /smith:insights scenario
• /smith:report → use /smith:insights report
• /smith:optimize spending → use /smith:insights spending analysis

Next Steps

After viewing insights:

• Take action: /smith:categorize to process new transactions
• Deep dive tax: /smith:tax deductions for tax-specific analysis
• Check health: /smith:health for overall financial health