Flux Analysis logo

Flux Analysis

Organization
vm0-ai
flux-analysis

Explain financial variances with driver analysis, period comparisons, waterfall bridges, and commentary.

Overview

Publishervm0-ai
Repositoryvm0-skills
Skill nameflux-analysis
Stars
76
Forks
18
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by vm0-ai on GitHub. Read the source before you install it.

Installation

Install the Flux Analysis AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/vm0-ai/vm0-skills.git /tmp/vm0-skills
mkdir -p .claude/skills
cp -r /tmp/vm0-skills/flux-analysis .claude/skills/flux-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Flux Analysis in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Flux Analysis on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Flux Analysis is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Decomposition Techniques

Price x Volume Separation

The foundational split for any metric expressible as unit price multiplied by quantity.

Two-factor formulas:

Total Movement = Actual Result - Baseline (budget or prior period)

Quantity Component  = (Actual Units - Baseline Units) x Baseline Unit Price
Pricing Component   = (Actual Unit Price - Baseline Unit Price) x Actual Units

Check: Quantity Component + Pricing Component = Total Movement
       (when the interaction term is absorbed into one of the two factors)

Three-factor formulas (isolating composition shifts):

Quantity Component    = (Actual Units - Baseline Units) x Baseline Price x Baseline Mix Weights
Pricing Component     = (Actual Price - Baseline Price) x Baseline Units x Actual Mix Weights
Composition Component = Baseline Price x Baseline Units x (Actual Mix Weights - Baseline Mix Weights)

Worked example — top-line revenue:

  • Baseline plan: 10,000 units at $50/unit = $500,000
  • Actual outcome: 11,000 units at $48/unit = $528,000
  • Net movement: +$28,000 favorable
    • Quantity uplift: +1,000 units x $50 = +$50,000 (favorable — higher volume)
    • Pricing drag: -$2 x 11,000 = -$22,000 (unfavorable — reduced average selling price)

Blended Rate / Composition Separation

Applicable when aggregated results blend multiple segments with distinct unit economics.

Formulas:

Rate Component = Sum across segments of [Actual Volume_i x (Actual Rate_i - Baseline Rate_i)]
Composition Component = Sum across segments of [Baseline Rate_i x (Actual Volume_i - Proportional Volume_i at Baseline Mix)]

Worked example — gross margin compression:

  • Segment X earns 60% margin; Segment Y earns 40% margin
  • Plan assumed a 50/50 split -> blended 50% margin
  • Actual split was 40/60 -> blended 48% margin
  • The 2-point margin decline is attributable to the shift toward the lower-margin segment

People-Cost Decomposition

Purpose-built for analyzing compensation and headcount-driven expense lines.

Total Compensation Movement = Actual Spend - Planned Spend

Break into:
1. Staffing level effect     = (Actual Headcount - Plan Headcount) x Plan Average Cost
2. Per-capita cost effect    = (Actual Average Cost - Plan Average Cost) x Plan Headcount
3. Composition effect        = Residual from shifts in seniority, department, or geography mix
4. Phasing effect            = Impact of hires arriving earlier or later than the plan assumed
5. Attrition benefit         = Savings from unplanned departures (partially offset by replacement and vacancy costs)

Functional Expense Decomposition

For operating cost categories where a price-times-volume model does not apply naturally.

Total OpEx Movement = Actual Operating Costs - Planned Operating Costs

Segment into:
1. Headcount-linked costs       (wages, benefits, payroll taxes, recruiting fees)
2. Activity-linked costs        (cloud hosting, payment processing fees, sales commissions, freight)
3. Discretionary programs       (travel, conferences, outside services, campaign spend)
4. Committed / fixed costs      (facility leases, insurance, enterprise software licenses)
5. Non-recurring charges        (severance, litigation, asset write-downs, project-specific outlays)
6. Timing / phasing differences (spend that shifted between periods relative to the plan)

Significance Thresholds & Prioritization

Calibrating Thresholds

Thresholds govern which movements warrant formal investigation and written explanation. Base them on:

  1. Overall materiality: Usually 1-5% of a primary benchmark (revenue, total assets, or net income)
  2. Relative line-item scale: Apply tighter percentage gates to larger balances
  3. Historical volatility: Allow wider bands for inherently variable accounts to filter noise
  4. Decision relevance: Would this size of movement influence a management decision or board discussion?

Suggested Threshold Grid

Comparison BasisSuggested Dollar GateSuggested Percentage GateTrigger Logic
Actual vs. annual planEntity-specific10%Whichever is breached first
Actual vs. same period last yearEntity-specific15%Whichever is breached first
Actual vs. latest forecastEntity-specific5%Whichever is breached first
Sequential month-over-monthEntity-specific20%Whichever is breached first

Set the dollar gate at roughly 0.5-1% of revenue for income-statement lines.

Triage Order When Multiple Items Exceed Thresholds

  1. Greatest absolute dollar impact — largest influence on the bottom line
  2. Greatest percentage deviation — may signal a process breakdown or data error
  3. Counter-trend movements — direction opposite to what history or forecasts predicted
  4. Newly emerged variances — items previously on track that have just diverged
  5. Compounding variances — gaps that have widened in each of the last several periods

Writing Effective Variance Narratives

Recommended Structure

[Line Item]: [Favorable / Unfavorable] movement of $[amount] ([X]%)
relative to [budget / prior period / forecast] for [reporting period]

Primary driver: [Brief label]
[Two to three sentences explaining the business cause, quantifying each
contributing factor where possible.]

Outlook: [One-time event / Likely to persist / Improving / Worsening]
Next step: [No action / Monitor / Deeper review / Adjust forecast]

Quality Criteria

Strong narratives consistently satisfy these tests:

  • Precise: Names concrete factors rather than restating the variance itself
  • Measured: Attaches dollar or percentage weight to each cited driver
  • Explanatory: Addresses why the movement occurred, not merely that it did
  • Prospective: States whether the movement is expected to continue, reverse, or evolve
  • Directive: Identifies any follow-up action or decision prompted by the finding
  • Compact: Two to four sentences — not padded filler

Pitfalls to Avoid

  • Restating the outcome as its own cause ("Revenue rose because revenue was higher")
  • Labeling a variance as "timing" without specifying what shifted and when normalization is expected
  • Calling something "one-time" without describing the actual event
  • Sweeping a material movement under "various small items" instead of decomposing further
  • Explaining only the dominant driver while ignoring meaningful offsets
  • Using vague qualifiers ("elevated," "slightly higher") without attached numbers

Bridge / Waterfall Presentation

Concept

A bridge (waterfall) chart traces the path from a starting value to an ending value through a sequence of additive and subtractive contributors. It is the visual companion to variance decomposition.

Data Architecture

Starting point:   [Baseline figure — plan, prior period, or forecast]
Contributors:     [Ordered list of signed driver amounts]
Ending point:     [Actual figure]

Integrity check:  Starting point + Sum(all contributors) = Ending point

Text-Format Bridge (When No Charting Tool Is Available)

BRIDGE: Operating Expenses — Q4 Actual vs. Q4 Plan

Q4 Planned OpEx                                       $8,000K
  |
  |--[+] Incremental headcount above plan              +$500K
  |--[+] Unplanned outside counsel fees                +$200K
  |--[-] Open-role savings (delayed hiring)            -$350K
  |--[-] Travel spend below budget                     -$180K
  |--[+] Cloud infrastructure overrun                  +$130K
  |--[-] Marketing program deferrals                   -$100K
  |
Q4 Actual OpEx                                        $8,200K

Net Movement: +$200K (+2.5% unfavorable)

Companion Reconciliation Table

DriverAmountShare of Total MovementRunning Total
Incremental headcount+$500K250%+$500K
Outside counsel+$200K100%+$700K
Open-role savings-$350K-175%+$350K
Travel underspend-$180K-90%+$170K
Cloud overrun+$130K65%+$300K
Marketing deferrals-$100K-50%+$200K
Net movement+$200K100%

Individual shares can exceed 100% when favorable and unfavorable drivers offset each other.

Presentation Guidelines

  1. Sequence drivers from most favorable to most unfavorable (or in a logical business narrative order)
  2. Cap the driver count at 5-8; roll smaller items into an "All other" bucket
  3. Verify arithmetic: opening value plus all drivers equals closing value
  4. Use color to distinguish direction — green for favorable, red for unfavorable — in graphical renderings
  5. Annotate each segment with both the dollar amount and a short label
  6. Include a summary segment showing the net total movement

Multi-Scenario Comparisons

Three-Column Layout

Line ItemAnnual PlanLatest ForecastActualPlan Var ($)Plan Var (%)Forecast Var ($)Forecast Var (%)
Revenue$X$X$X$XX%$XX%
Direct costs$X$X$X$XX%$XX%
Gross profit$X$X$X$XX%$XX%

Choosing the Right Baseline

  • Actual vs. annual plan: Governance and incentive evaluation; the plan is fixed at the start of the fiscal year
  • Actual vs. rolling forecast: Operational steering and early-warning detection; the forecast is refreshed monthly or quarterly
  • Forecast vs. plan: Gauges how management expectations have shifted since planning; highlights planning-accuracy gaps
  • Actual vs. prior period (sequential): Reveals trend direction; especially useful for new ventures or post-acquisition integration where a plan may not yet exist
  • Actual vs. prior year (year-over-year): Growth assessment adjusted for seasonality

Tracking Forecast Precision

Measure forecast quality over time to tighten future planning:

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

MAPE (Mean Absolute Percentage Error) = Mean of |Actual - Forecast| / |Actual| across all periods
MonthForecastActualDeviationAccuracy
Jan$X$X$X (X%)XX%
Feb$X$X$X (X%)XX%
...............
Full YearMAPEXX%

Reading Variance Trends Across Time

  • Persistently favorable: Plans may be overly conservative (potential sandbagging)
  • Persistently unfavorable: Targets may be unrealistic or execution is lagging
  • Widening unfavorable gap: Performance is deteriorating or external conditions are shifting
  • Narrowing gap: Forecast accuracy is improving through the year (a healthy signal)
  • Erratic swings: Business is inherently unpredictable or the forecasting methodology needs refinement

Frequently asked questions

What does the Flux Analysis AI skill do?

Explain financial variances with driver analysis, period comparisons, waterfall bridges, and commentary.

Why use Flux Analysis on TypingMind?

Because you install it once and use it with any model. Flux Analysis is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Flux Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vm0-ai/vm0-skills/tree/main/flux-analysis. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Flux Analysis?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Flux Analysis?

As many as you like. As long as a model supports skills, you can use Flux Analysis with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Flux Analysis AI skill free?

It is published on GitHub by vm0-ai. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇