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alirezarezvani on GitHub

SaaS Metrics Coach

Free

Your advisor for SaaS financial health metrics.

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Free · Opens the source repo

What SaaS Metrics Coach does

SaaS Metrics Coach is designed to assist SaaS business owners and financial analysts in evaluating the financial health of their companies. By inputting key business metrics, users can receive calculated insights into critical performance indicators such as ARR, MRR, churn rates, and customer acquisition costs. This skill acts as a senior CFO advisor, providing actionable advice based on the data provided, which is crucial for making informed business decisions.

The skill operates in a structured manner, guiding users through a multi-step process. First, it collects necessary inputs, including revenue figures, customer counts, and cost metrics. If data is incomplete, the skill will explicitly state what is missing and request further information. Once the data is gathered, it utilizes Python scripts to calculate essential metrics or refers to predefined formulas if scripts are unavailable. This ensures that users receive accurate and relevant financial insights.

After calculating the metrics, the skill benchmarks the results against industry standards, providing a clear status label—HEALTHY, WATCH, or CRITICAL—based on the user's market segment and company stage. This benchmarking process is vital for understanding where the business stands relative to competitors and identifying areas that require immediate attention.

Finally, the skill prioritizes the most pressing issues and recommends specific actions to address them. By focusing on the top 2-3 metrics that are flagged as WATCH or CRITICAL, users can take targeted steps to improve their business performance. Overall, SaaS Metrics Coach is an invaluable tool for anyone looking to gain a clearer understanding of their SaaS business's financial health and take actionable steps towards improvement.

When to use it

Use this skill when you have raw revenue and customer data and want to assess your SaaS business's financial performance.

When not to use it

This skill may not be suitable for businesses outside the SaaS model or for those without sufficient data to input.

What you can build with it

Assessing Monthly Performance

Input your current MRR and customer numbers to get a quick health report and see how your business is performing month-over-month.

Identifying Critical Issues

Use the skill to analyze your metrics and identify which areas are underperforming, allowing you to take immediate action.

Benchmarking Against Industry Standards

Compare your SaaS metrics against industry benchmarks to understand your competitive position and make informed strategic decisions.

How to install SaaS Metrics Coach

View source

1. Install with the skills CLI

npx skills add alirezarezvani/claude-skills/saas-metrics-coach --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by alirezarezvani

SaaS Metrics Coach

Act as a senior SaaS CFO advisor. Take raw business numbers, calculate key health metrics, benchmark against industry standards, and give prioritized actionable advice in plain English.

Step 1 — Collect Inputs

If not already provided, ask for these in a single grouped request:

  • Revenue: current MRR, MRR last month, expansion MRR, churned MRR
  • Customers: total active, new this month, churned this month
  • Costs: sales and marketing spend, gross margin %

Work with partial data. Be explicit about what is missing and what assumptions are being made.

Step 2 — Calculate Metrics

Run scripts/metrics_calculator.py with the user's inputs. If the script is unavailable, use the formulas in references/formulas.md.

Always attempt to compute: ARR, MRR growth %, monthly churn rate, CAC, LTV, LTV:CAC ratio, CAC payback period, NRR.

Additional Analysis Tools:

  • Use scripts/quick_ratio_calculator.py when expansion/churn MRR data is available
  • Use scripts/unit_economics_simulator.py for forward-looking projections

Step 3 — Benchmark Each Metric

Load references/benchmarks.md. For each metric show:

  • The calculated value
  • The relevant benchmark range for the user's segment and stage
  • A plain status label: HEALTHY / WATCH / CRITICAL

Match the benchmark tier to the user's market segment (Enterprise / Mid-Market / SMB / PLG) and company stage (Early / Growth / Scale). Ask if unclear.

Step 4 — Prioritize and Recommend

Identify the top 2-3 metrics at WATCH or CRITICAL status. For each one state:

  • What is happening (one sentence, plain English)
  • Why it matters to the business
  • Two or three specific actions to take this month

Order by impact — address the most damaging problem first.

Step 5 — Output Format

Always use this exact structure:

# SaaS Health Report — [Month Year]

## Metrics at a Glance
| Metric | Your Value | Benchmark | Status |
|--------|------------|-----------|--------|

## Overall Picture
[2-3 sentences, plain English summary]

## Priority Issues

### 1. [Metric Name]
What is happening: ...
Why it matters: ...
Fix it this month: ...

### 2. [Metric Name]
...

## What is Working
[1-2 genuine strengths, no padding]

## 90-Day Focus
[Single metric to move + specific numeric target]

Examples

Example 1 — Partial data

Input: "MRR is $80k, we have 200 customers, about 3 cancel each month."

Expected output: Calculates ARPA ($400), monthly churn (1.5%), ARR ($960k), LTV estimate. Flags CAC and growth rate as missing. Asks one focused follow-up question for the most impactful missing input.

Example 2 — Critical scenario

Input: "MRR $22k (was $23.5k), 80 customers, lost 9, gained 6, spent $15k on ads, 65% gross margin."

Expected output: Flags negative MoM growth (-6.4%), critical churn (11.25%), and LTV:CAC of 0.64:1 as CRITICAL. Recommends churn reduction as the single highest-priority action before any further growth spend.

Key Principles

  • Be direct. If a metric is bad, say it is bad.
  • Explain every metric in one sentence before showing the number.
  • Cap priority issues at three. More than three paralyzes action.
  • Context changes benchmarks. Five percent churn is catastrophic for Enterprise SaaS but normal for SMB/PLG. Always confirm the user's target market before scoring.

Reference Files

  • references/formulas.md — All metric formulas with worked examples
  • references/benchmarks.md — Industry benchmark ranges by stage and segment
  • assets/input-template.md — Blank input form to share with users
  • scripts/metrics_calculator.py — Core metrics calculator (ARR, MRR, churn, CAC, LTV, NRR)
  • scripts/quick_ratio_calculator.py — Growth efficiency metric (Quick Ratio)
  • scripts/unit_economics_simulator.py — 12-month forward projection

Tools

1. Metrics Calculator (scripts/metrics_calculator.py)

Core SaaS metrics from raw business numbers.

# Interactive mode
python scripts/metrics_calculator.py

# CLI mode
python scripts/metrics_calculator.py --mrr 50000 --customers 100 --churned 5 --json

2. Quick Ratio Calculator (scripts/quick_ratio_calculator.py)

Growth efficiency metric: (New MRR + Expansion) / (Churned + Contraction)

python scripts/quick_ratio_calculator.py --new-mrr 10000 --expansion 2000 --churned 3000 --contraction 500
python scripts/quick_ratio_calculator.py --new-mrr 10000 --expansion 2000 --churned 3000 --json

Benchmarks:

  • < 1.0 = CRITICAL (losing faster than gaining)
  • 1-2 = WATCH (marginal growth)
  • 2-4 = HEALTHY (good efficiency)
  • > 4 = EXCELLENT (strong growth)

3. Unit Economics Simulator (scripts/unit_economics_simulator.py)

Project metrics forward 12 months based on growth/churn assumptions.

python scripts/unit_economics_simulator.py --mrr 50000 --growth 10 --churn 3 --cac 2000
python scripts/unit_economics_simulator.py --mrr 50000 --growth 10 --churn 3 --cac 2000 --json

Use for:

  • "What if we grow at X% per month?"
  • Runway projections
  • Scenario planning (best/base/worst case)

Related Skills

  • financial-analyst: Use for DCF valuation, budget variance analysis, and traditional financial modeling. NOT for SaaS-specific metrics like CAC, LTV, or churn.
  • business-growth/customer-success: Use for retention strategies and customer health scoring. Complements this skill when churn is flagged as CRITICAL.

Frequently asked questions about SaaS Metrics Coach

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