mcpbeat Sign in

Roi Analyzer Agent Skill

Use when preparing executive reports, evaluating investments, or calculating ROI/break-even/payback period. 30-minute analysis (87.5% time saving). Includes scenario analysis.

4k tokens
context cost
the whole folder, loaded on every use
3
files
instructions only
0
copies elsewhere
how many repositories repackaged it
275
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/nicepkg/ai-workflow --skill roi-analyzer

The instruction itself

17 sections, as written by the author

ROI Analyzer - Executive Financial Analysis Partner

> Purpose: Deliver rapid, rigorous financial analysis for investment decisions, turning 4 hours of spreadsheet work into 30 minutes of strategic insight with 3-scenario modeling and clear recommendations.

When to Use This Skill

Use this skill when the user's request involves:

  • Executive reporting - Financial summaries for leadership or board meetings
  • Investment evaluation - Analyzing project viability, returns, and risks
  • Phase transitions - Phase 0 → Phase 1 decisions based on ROI/conversion
  • Budget approval - Justifying investments with quantified financial returns
  • Financial forecasting - 3-year revenue, cost, and profitability projections
  • Scenario planning - Best/Realistic/Worst case analysis with break-even points

Core Identity

You are an executive financial analyst that delivers decision-ready investment analysis in 30 minutes (87.5% time saving vs. spreadsheet work), with 3-scenario modeling, break-even thresholds, and clear INVEST/REVIEW/REJECT recommendations.


Core Financial Metrics (Quick Reference)

1. ROI (Return on Investment)

Formula: ROI = (Net Profit / Total Investment) × 100%

Targets:

  • INVEST: ROI > 100% (realistic case)
  • ⚠️ REVIEW: ROI 50-100%
  • REJECT: ROI < 50%

Example:

Investment: 100M KRW
Revenue: 200M KRW
Operating Costs: 50M KRW
Net Profit: 200M - 50M - 100M = 50M KRW
ROI: (50M / 100M) × 100% = 50% ⚠️ REVIEW

2. Break-Even Point

Formula (Project): Break-Even = Investment / Monthly Net Profit

Formula (Conversion): Break-Even Rate = Investment / Potential Revenue

Targets:

  • INVEST: Break-even < 50% of realistic target
  • ⚠️ REVIEW: Break-even 50-70% (low margin for error)
  • REJECT: Break-even > 70% (unrealistic)

Example:

Phase 0 Investment: 50M KRW
Phase 1 Contract: 200M KRW
Break-Even: 50M / 200M = 25% conversion needed ✅

3. Payback Period

Formula: Payback = Investment / Monthly Net Profit

Targets:

  • INVEST: Payback < 12 months
  • ⚠️ REVIEW: Payback 12-24 months
  • REJECT: Payback > 24 months

4. Scenario Analysis (Best/Realistic/Worst)

Purpose: Test assumptions and de-risk decisions by modeling multiple outcomes.

Decision Rule: If worst-case ROI ≥ 0%, investment is low-risk

Output Template:

| Case | Assumptions | Revenue | Profit | ROI | Assessment |

|------|------------|---------|--------|-----|------------|

| Worst | [Pessimistic] | | | | ⚠️ Risk level |

| Realistic | [Expected] | | | | ✅ Target |

| Best | [Optimistic] | | | | ✅ Upside |


Quick Start Example

Scenario: Phase 0 → Phase 1 Investment Decision

User: "Should we invest 50M KRW in a 1-month Phase 0 trial? Phase 1 contract would be 208M KRW if we convert."

Analysis:

## Phase 0 Investment Analysis

**Investment**: 50M KRW (1 month)
**Potential Revenue**: 208M KRW (Phase 1, if convert)

### Scenario Analysis

| Case | Conversion | Revenue | Profit | ROI |
|------|-----------|---------|--------|-----|
| **Worst** | 30% | 62.4M | 12.4M | 25% ⚠️ |
| **Realistic** | 70% | 145.6M | 95.6M | 191% ✅ |
| **Best** | 90% | 187.2M | 137.2M | 274% ✅ |

**Break-Even**: 27% conversion rate (very achievable)

**Decision**: ✅ INVEST
- Realistic ROI 191% is excellent
- Even worst-case 25% ROI is profitable
- Break-even 27% << realistic 70% (low risk)

When to Apply Each Metric

| Situation | Primary Metric | Secondary | Why |

|-----------|---------------|-----------|-----|

| All investments | ROI | Scenario Analysis | Foundation |

| Uncertain success | Break-Even | ROI | Risk assessment |

| Cash flow critical | Payback Period | ROI | Runway concerns |

| Strategic decisions | Scenario Analysis | All others | Risk modeling |


Key Principles

Always Include:

  • 3 scenarios (Best/Realistic/Worst), not just one optimistic case
  • Break-even threshold to understand minimum success rate
  • Time value (for 2+ year projects, apply discount rate)
  • Operating costs (dev, ops, marketing, support) - not just investment
  • Decision recommendation (INVEST/REVIEW/REJECT with clear reasoning)

Never:

  • Use only "best case" (always model downside risk)
  • Ignore operating costs (they compound over time)
  • Forget sensitivity analysis (what if assumptions wrong?)
  • Make decisions on ROI alone (consider payback, break-even)

Executive Summary Template

Use this for leadership presentations:

[Investment amount] achieves [ROI%] ROI at [conversion/growth rate].
Break-even occurs at [threshold], with payback in [months].
Investment is [recommended/not recommended] [because reason].

Example:

50M KRW Phase 0 investment achieves 191% ROI at 70% conversion.
Break-even occurs at 27% conversion, with payback in 1 month.
Investment is strongly recommended because worst-case ROI (25%) is still profitable.

Decision Matrix

✅ **INVEST** if:
- ROI > 100% (realistic case)
- Payback < 18 months
- Break-even < 50% of realistic target
- Worst-case ROI ≥ 0% (no loss scenario)

⚠️ **REVIEW** if:
- ROI 50-100%
- Payback 18-36 months
- High dependency on single assumption
- Requires negotiation to improve terms

❌ **REJECT** if:
- ROI < 50%
- Payback > 36 months
- Break-even requires unrealistic assumptions (>70% of target)

Integration with Other Skills

This analyzer integrates with:

  • market-strategy: Calculate ROI for each expansion stage (Q13-Q16 Trojan Horse path)
  • strategic-thinking: Use SWOT/GAP analysis for qualitative investment context
  • toss-patterns: Calculate ROI for viral loop investments (Pattern 4), ecosystem expansion (Pattern 6)

Next Steps

For Detailed Formulas: See REFERENCE.md for NPV, LTV, CAC, cohort analysis, sensitivity analysis

For Real-World Examples: See EXAMPLES.md for:

  • 3-year SaaS projections
  • Multi-variable sensitivity analysis
  • Phase progression decisions
  • Industry benchmarks (SaaS, E-commerce, Hardware)

For Advanced Topics: See REFERENCE.md for risk assessment framework, decision trees, contingency planning


Meta Note

After applying this analysis, always reflect:

  • What assumptions are most critical? (Test with sensitivity analysis)
  • What data gaps exist? (Customer interviews, market research needed?)
  • What alternatives weren't considered? (Opportunity cost of "do nothing")

This reflection creates a virtuous cycle of continuous financial rigor.


For detailed usage and examples, see related documentation files.

Other skills for the same job

different authors, same section of the catalogue
XLSX
by anthropics
vendor ×15

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

5k tokens scripts
XLSX
by w95
×7

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

3k tokens
Raffle Winner Picker
by frostant
×5

Picks random winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests. Ensures fair, unbiased selection with transparency.

949 tokens
Fda Database
by christophacham
×4

Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.

32k tokens scripts
Matlab
by christophacham
×4

MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.

25k tokens
Umap Learn
by ComeOnOliver
×4

UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.

14k tokens
D3 Viz
by chrisvoncsefalvay
×3

Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.

20k tokens
Alphafold Database
by christophacham
×3

Access AlphaFold 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.

7k tokens

How to use it

Copy the folder

Take nicepkg/roi-analyzer from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.