Agent skill

Variance Analysis

by majiayu000 in majiayu000/claude-skill-registry

Decompose financial variances into drivers with narrative explanations and waterfall analysis.

MITAuto-check passedBusiness, Finance & HR

Install Variance Analysis

skills CLI
$ npx skills add majiayu000/claude-skill-registry --skill variance-analysis -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install majiayu000/claude-skill-registry variance-analysis --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analysis/variance-analysis-yongjianwan-agentskill .claude/skills/variance-analysis && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
variance-analysis
GitHub stars
666
Used in
3 other repos
Token cost
~2.8k tokens
SKILL.md length
914 words
Files
2
Skills in repo
971
Repo updated
First seen
Licence
MIT

At a glance

Decompose financial variances into drivers with narrative explanations and waterfall analysis.

  • Works in 4 steps: Financial statement materiality:… → Line item size: Larger line items… → Volatility: More volatile line items may… → …
  • Analyzing budget vs
  • SKILL.md covers Variance Decomposition…, Materiality Thresholds and…, Narrative Generation for… and Waterfall Chart Methodology, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Variance Analysis is an agent skill from majiayu000/claude-skill-registry. Decompose financial variances into drivers with narrative explanations and waterfall analysis. Use when analyzing budget vs. actual, period-over-period changes, revenue or expense variances, or preparing variance commentary for leadership.

Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `metadata.json`).

It sits in Business, Finance & HR, covering Financial analysis. The repository describes itself as: Searchable Claude Code skills catalog with source-linked guides and generated registry artifacts. The licence is MIT.

When your agent uses it

  • Analyzing budget vs
  • Tasks that involve Financial analysis

Example prompts

  • “/variance-analysis”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Financial statement materiality: Typically 1-5% of a key benchmark (revenue, total assets, net income)
  2. Line item size: Larger line items warrant lower percentage thresholds
  3. Volatility: More volatile line items may need higher thresholds to avoid noise
  4. Management attention: What level of variance would change a decision?

What it can do on your machine

Read from SKILL.md and the folder at commit 000116a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Variance Analysis loads about 2.8k tokens when it runs. Until then it costs about 64 tokens; SKILL.md has 914 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~64
When it runs · the whole SKILL.md, loaded when a task matches
~2.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from majiayu000/claude-skill-registry at commit 000116a, republished under its MIT licence (© majiayu000). 914 words, ~2,787 tokens.

Download SKILL.mdSave it as .claude/skills/variance-analysis/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
variance-analysis
description
Decompose financial variances into drivers with narrative explanations and waterfall analysis. Use when analyzing budget vs. actual, period-over-period changes, revenue or expense variances, or preparing variance commentary for leadership.

Variance Analysis

Important: This skill assists with variance analysis workflows but does not provide financial advice. All analyses should be reviewed by qualified financial professionals before use in reporting.

Techniques for decomposing variances, materiality thresholds, narrative generation, waterfall chart methodology, and budget vs actual vs forecast comparisons.

Variance Decomposition Techniques

Price / Volume Decomposition

The most fundamental variance decomposition. Used for revenue, cost of goods, and any metric that can be expressed as Price x Volume.

Formula:

Total Variance = Actual - Budget (or Prior)

Volume Effect  = (Actual Volume - Budget Volume) x Budget Price
Price Effect   = (Actual Price - Budget Price) x Actual Volume
Mix Effect     = Residual (interaction term), or allocated proportionally

Verification:  Volume Effect + Price Effect = Total Variance
               (when mix is embedded in the price/volume terms)

Three-way decomposition (separating mix):

Volume Effect = (Actual Volume - Budget Volume) x Budget Price x Budget Mix
Price Effect  = (Actual Price - Budget Price) x Budget Volume x Actual Mix
Mix Effect    = Budget Price x Budget Volume x (Actual Mix - Budget Mix)

Example — Revenue variance:

  • Budget: 10,000 units at $50 = $500,000
  • Actual: 11,000 units at $48 = $528,000
  • Total variance: +$28,000 favorable
    • Volume effect: +1,000 units x $50 = +$50,000 (favorable — sold more units)
    • Price effect: -$2 x 11,000 units = -$22,000 (unfavorable — lower ASP)
    • Net: +$28,000
Rate / Mix Decomposition

Used when analyzing blended rates across segments with different unit economics.

Formula:

Rate Effect = Sum of (Actual Volume_i x (Actual Rate_i - Budget Rate_i))
Mix Effect  = Sum of (Budget Rate_i x (Actual Volume_i - Expected Volume_i at Budget Mix))

Example — Gross margin variance:

  • Product A: 60% margin, Product B: 40% margin
  • Budget mix: 50% A, 50% B → Blended margin 50%
  • Actual mix: 40% A, 60% B → Blended margin 48%
  • Mix effect explains 2pp of margin compression
Headcount / Compensation Decomposition

Used for analyzing payroll and people-cost variances.

Total Comp Variance = Actual Compensation - Budget Compensation

Decompose into:
1. Headcount variance    = (Actual HC - Budget HC) x Budget Avg Comp
2. Rate variance         = (Actual Avg Comp - Budget Avg Comp) x Budget HC
3. Mix variance          = Difference due to level/department mix shift
4. Timing variance       = Hiring earlier/later than planned (partial-period effect)
5. Attrition impact      = Savings from unplanned departures (partially offset by backfill costs)
Spend Category Decomposition

Used for operating expense analysis when price/volume is not applicable.

Total OpEx Variance = Actual OpEx - Budget OpEx

Decompose by:
1. Headcount-driven costs    (salaries, benefits, payroll taxes, recruiting)
2. Volume-driven costs       (hosting, transaction fees, commissions, shipping)
3. Discretionary spend       (travel, events, professional services, marketing programs)
4. Contractual/fixed costs   (rent, insurance, software licenses, subscriptions)
5. One-time / non-recurring  (severance, legal settlements, write-offs, project costs)
6. Timing / phasing          (spend shifted between periods vs plan)

Materiality Thresholds and Investigation Triggers

Setting Thresholds

Materiality thresholds determine which variances require investigation and narrative explanation. Set thresholds based on:

  1. Financial statement materiality: Typically 1-5% of a key benchmark (revenue, total assets, net income)
  2. Line item size: Larger line items warrant lower percentage thresholds
  3. Volatility: More volatile line items may need higher thresholds to avoid noise
  4. Management attention: What level of variance would change a decision?
Comparison TypeDollar ThresholdPercentage ThresholdTrigger
Actual vs BudgetOrganization-specific10%Either exceeded
Actual vs Prior PeriodOrganization-specific15%Either exceeded
Actual vs ForecastOrganization-specific5%Either exceeded
Sequential (MoM)Organization-specific20%Either exceeded

Set dollar thresholds based on your organization's size. Common practice: 0.5%-1% of revenue for income statement items.

Investigation Priority

When multiple variances exceed thresholds, prioritize investigation by:

  1. Largest absolute dollar variance — biggest P&L impact
  2. Largest percentage variance — may indicate process issue or error
  3. Unexpected direction — variance opposite to trend or expectation
  4. New variance — item that was on track and is now off
  5. Cumulative/trending variance — growing each period

Narrative Generation for Variance Explanations

Structure for Each Variance Narrative
[Line Item]: [Favorable/Unfavorable] variance of $[amount] ([percentage]%)
vs [comparison basis] for [period]

Driver: [Primary driver description]
[2-3 sentences explaining the business reason for the variance, with specific
quantification of contributing factors]

Outlook: [One-time / Expected to continue / Improving / Deteriorating]
Action: [None required / Monitor / Investigate further / Update forecast]
Narrative Quality Checklist

Good variance narratives should be:

  • Specific: Names the actual driver, not just "higher than expected"
  • Quantified: Includes dollar and percentage impact of each driver
  • Causal: Explains WHY it happened, not just WHAT happened
  • Forward-looking: States whether the variance is expected to continue
  • Actionable: Identifies any required follow-up or decision
  • Concise: 2-4 sentences, not a paragraph of filler
Common Narrative Anti-Patterns to Avoid
  • "Revenue was higher than budget due to higher revenue" (circular — no actual explanation)
  • "Expenses were elevated this period" (vague — which expenses? why?)
  • "Timing" without specifying what was early/late and when it will normalize
  • "One-time" without explaining what the item was
  • "Various small items" for a material variance (must decompose further)
  • Focusing only on the largest driver and ignoring offsetting items

Waterfall Chart Methodology

Concept

A waterfall (or bridge) chart shows how you get from one value to another through a series of positive and negative contributors. Used to visualize variance decomposition.

Data Structure
Starting value:  [Base/Budget/Prior period amount]
Drivers:         [List of contributing factors with signed amounts]
Ending value:    [Actual/Current period amount]

Verification:    Starting value + Sum of all drivers = Ending value
Show full SKILL.md (368 more words)Show less
Text-Based Waterfall Format

When a charting tool is not available, present as a text waterfall:

WATERFALL: Revenue — Q4 Actual vs Q4 Budget

Q4 Budget Revenue                                    $10,000K
  |
  |--[+] Volume growth (new customers)               +$800K
  |--[+] Expansion revenue (existing customers)      +$400K
  |--[-] Price reductions / discounting               -$200K
  |--[-] Churn / contraction                          -$350K
  |--[+] FX tailwind                                  +$50K
  |--[-] Timing (deals slipped to Q1)                 -$150K
  |
Q4 Actual Revenue                                    $10,550K

Net Variance: +$550K (+5.5% favorable)
Bridge Reconciliation Table

Complement the waterfall with a reconciliation table:

DriverAmount% of VarianceCumulative
Volume growth+$800K145%+$800K
Expansion revenue+$400K73%+$1,200K
Price reductions-$200K-36%+$1,000K
Churn / contraction-$350K-64%+$650K
FX tailwind+$50K9%+$700K
Timing (deal slippage)-$150K-27%+$550K
Total variance+$550K100%

Note: Percentages can exceed 100% for individual drivers when there are offsetting items.

Waterfall Best Practices
  1. Order drivers from largest positive to largest negative (or in logical business sequence)
  2. Keep to 5-8 drivers maximum — aggregate smaller items into "Other"
  3. Verify the waterfall reconciles (start + drivers = end)
  4. Color-code: green for favorable, red for unfavorable (in visual charts)
  5. Label each bar with both the amount and a brief description
  6. Include a "Total Variance" summary bar

Budget vs Actual vs Forecast Comparisons

Three-Way Comparison Framework
MetricBudgetForecastActualBud Var ($)Bud Var (%)Fcast Var ($)Fcast Var (%)
Revenue$X$X$X$XX%$XX%
COGS$X$X$X$XX%$XX%
Gross Profit$X$X$X$XX%$XX%
When to Use Each Comparison
  • Actual vs Budget: Annual performance measurement, compensation decisions, board reporting. Budget is set at the beginning of the year and typically not changed.
  • Actual vs Forecast: Operational management, identifying emerging issues. Forecast is updated periodically (monthly or quarterly) to reflect current expectations.
  • Forecast vs Budget: Understanding how expectations have changed since planning. Useful for identifying planning accuracy issues.
  • Actual vs Prior Period: Trend analysis, sequential performance. Useful when budget is not meaningful (new business lines, post-acquisition).
  • Actual vs Prior Year: Year-over-year growth analysis, seasonality-adjusted comparison.
Forecast Accuracy Analysis

Track how accurate forecasts are over time to improve planning:

Forecast Accuracy = 1 - |Actual - Forecast| / |Actual|

MAPE (Mean Absolute Percentage Error) = Average of |Actual - Forecast| / |Actual| across periods
PeriodForecastActualVarianceAccuracy
Jan$X$X$X (X%)XX%
Feb$X$X$X (X%)XX%
...............
AvgMAPEXX%

Track how variances evolve over the year to identify systematic bias:

  • Consistently favorable: Budget may be too conservative (sandbagging)
  • Consistently unfavorable: Budget may be too aggressive or execution issues
  • Growing unfavorable: Deteriorating performance or unrealistic targets
  • Shrinking variance: Forecast accuracy improving through the year (normal pattern)
  • Volatile: Unpredictable business or poor forecasting methodology

© majiayu000, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/analysis/variance-analysis-yongjianwan-agentskill of majiayu000/claude-skill-registry.

  • SKILL.md
  • metadata.json

Open the folder on GitHubat commit 000116a

Used in 3 other repositories

We found 4 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in majiayu000/claude-skill-registry, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Variance Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Variance Analysis compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Variance Analysis this skillmajiayu000/claude-skill-registry6663 repos~2.8kAutomated safety check: PassMIT
Financial Analyzinghuangjia2019/claude-code-engineering1.1k1 repos~474Automated safety check: PassNone
Longbridge Earningshelsome/folio2691 repos~2.5kAutomated safety check: PassNone
Earnings AnalysisWind-Alice/AliceMarket1283 repos~2.2kAutomated safety check: PassNone
Buy Side Equity Research Memohaskaomni/serenity-skill632—~3.8kAutomated safety check: PassMIT
Fundamentalsstaskh/trading_skills374—~836Automated safety check: PassMIT

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Questions about Variance Analysis

What does Variance Analysis do?

Decompose financial variances into drivers with narrative explanations and waterfall analysis. Variance Analysis is an agent skill from majiayu000/claude-skill-registry. Decompose financial variances into drivers with narrative explanations and waterfall analysis.

When should I use Variance Analysis?

Variance Analysis fits situations like: analyzing budget vs; tasks that involve Financial analysis.

How do I install Variance Analysis in Claude Code?

Run `npx skills add majiayu000/claude-skill-registry --skill variance-analysis -a claude-code`. Or copy the skill folder (skills/analysis/variance-analysis-yongjianwan-agentskill in majiayu000/claude-skill-registry) into .claude/skills/variance-analysis in your project. Claude Code loads it when a task matches its description.

How do I install Variance Analysis in Codex?

Run `npx skills add majiayu000/claude-skill-registry --skill variance-analysis -a codex`. Or copy the skill folder (skills/analysis/variance-analysis-yongjianwan-agentskill in majiayu000/claude-skill-registry) into .agents/skills/variance-analysis in your project. Codex loads it when a task matches its description.

Can I use Variance Analysis in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add majiayu000/claude-skill-registry --skill variance-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/variance-analysis, .gemini/skills/variance-analysis, .github/skills/variance-analysis and .opencode/skills/variance-analysis in your project.

What does Variance Analysis need to run?

SKILL.md names no scripts, command-line tools or credentials: Variance Analysis is instructions for the agent only.

Does Variance Analysis access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Variance Analysis safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Variance Analysis use?

Variance Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Variance Analysis use?

About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Variance Analysis?

Skills that share tags, products or a category with Variance Analysis: Financial Analyzing (huangjia2019/claude-code-engineering, 1.1k stars), Longbridge Earnings (helsome/folio, 269 stars), Earnings Analysis (Wind-Alice/AliceMarket, 128 stars) and Buy Side Equity Research Memo (haskaomni/serenity-skill, 632 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Variance Analysis?

majiayu000 (a GitHub user) maintains it in majiayu000/claude-skill-registry, which has 666 GitHub stars. The repository holds 971 skills in this directory. The repository was last updated on October 7, 2026.

Source: majiayu000/claude-skill-registry on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.