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variance-analysis

Business
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Analyze period-over-period financial variance across channels

QUICK START

How to use this skill

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  2. Copy the prompt below and paste it into your agent.
  3. Review the proposed files and risks before you approve installation.
Prompt to paste
I want to install this Agent Skill for this project in Codex.

Source SKILL.md: https://github.com/majiayu000/claude-skill-registry/blob/HEAD/skills/analysis/variance-analysis-jocko-fuel-cowork-plugins/SKILL.md

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Copying this prompt does not install or run the skill. Review third-party files before use. Codex skill guide

You are helping the finance team understand period-over-period financial variances.

IMPORTANT: Before doing anything else, use the ToolSearch tool with query +snowflake to load the snowflake MCP tools. All tools below are prefixed with mcp__snowflake__ (e.g., mcp__snowflake__get_pnl_summary).

Follow these steps:

Step 1: Define Comparison

Ask the user:

  • Metric focus: Revenue, COGS, margin, or full P&L?
  • Current period: Which period to analyze? (e.g., "this month", "Q1 2026")
  • Comparison period: What to compare against? (e.g., "last month", "same month last year")
  • Channel: Specific channel or all?

Step 2: Pull Data for Both Periods

Use mcp__snowflake__get_pnl_summary for each period. Also use mcp__snowflake__get_channel_revenue if channel-level revenue detail is needed. Use mcp__snowflake__get_unit_economics for per-unit variance.

Step 3: Calculate Variances

For each metric, calculate:

  • Absolute variance — current period minus comparison period
  • Percentage variance — (current - comparison) / comparison * 100
  • Direction — favorable or unfavorable

Step 4: Root Cause Analysis

For the largest variances, investigate:

  • Is the variance driven by volume changes or price/cost changes?
  • Which channels or products are the biggest contributors?
  • Are there one-time items distorting the comparison?
  • Delegate to the forecast-root-cause-analyzer agent for deeper analysis if needed

Step 5: Present Results

Format as a variance report:

  • Summary table with current, prior, and variance columns
  • Top 3-5 drivers of the variance
  • Favorable vs unfavorable breakdown
  • Recommendations or areas requiring attention

Step 6: Follow-Up

Offer:

  • P&L report — /jf-financial-analyst:pnl-report
  • Scenario modeling — /jf-financial-analyst:scenario-model
  • Demand forecast — /jf-financial-analyst:forecast-demand

Error Handling

  • If Snowflake MCP is unavailable, inform the user and suggest checking the HORIZON_SNOWFLAKE_TOKEN
  • If comparison period data is incomplete, note which metrics can and cannot be compared