Finance Budget Variance Analysis

SkillCommerce & finance

Explain actual versus budget or prior-period performance with materiality thresholds, driver logic, and management-ready conclusions.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Finance Budget Variance Analysis skill

What this skill tells your AI

The instructions your AI receives, as published by contextgo/contextgo in src/process/resources/skills/finance-analyst-pack/skills/finance-budget-variance-analysis/SKILL.md and read by ahel’s review.

Use this skill when the finance task is really about movement and explanation.

Use when

  • The user asks why actuals missed or beat plan.
  • Management wants a clean bridge from top-line movement to root drivers.
  • You need a defensible explanation of variance rather than a raw table.

Do not use when

  • There is no comparison basis.
  • The movement is immaterial and the task is really just reporting.
  • Source files are too inconsistent to tell whether the numbers align.

Variance rules

  • Start with materiality, not with every line item.
  • Favorable or unfavorable depends on the line type.
  • Separate volume, price, mix, timing, and one-off effects where possible.
  • Do not over-explain immaterial noise.

Workflow

1. Set the comparison frame

Clarify:

  • actual vs budget, forecast, or prior period
  • month, quarter, year, or rolling view
  • the materiality threshold

If the threshold is not given, propose one and say so.

2. Identify the few variances that matter

Rank by:

  • absolute dollar impact
  • percentage deviation
  • business relevance

The answer should center on the biggest drivers, not every row.

3. Explain the drivers

For each material variance, test whether it comes from:

  • volume
  • price or rate
  • mix
  • timing
  • one-off or accounting reclassification

4. Close with control signals

End by stating:

  • what is a short-term variance
  • what is structural
  • what needs operating follow-up
  • what should change in the forecast

Output format

Return:

1. Variance frame

  • comparison basis
  • threshold
  • scope

2. Material drivers

  • line or area
  • variance amount and direction
  • likely explanation
  • confidence level

3. Management readout

  • what truly moved
  • what is noise
  • what follow-up or reforecast is needed

Use together with

  • finance-financial-statement-analysis
  • office-source-reconciliation
  • office-duckdb-query

Signals

GitHub stars
54
Forks
5
Last commit
May 2026
Advanced
Catalog kind
skill
Gateway key
finance-budget-variance-analysis
Source
github.com/contextgo/contextgo