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Agent skill

Startup Metrics Framework

by wshobson in wshobson/agents

Track, calculate, and optimize key performance metrics for SaaS, marketplace, consumer, and B2B startups from seed through Series A, including unit economics, growth efficiency, and cash management.

MITAuto-check passedBusiness, Finance & HR

Install Startup Metrics Framework

skills CLI
$ npx skills add wshobson/agents --skill startup-metrics-framework -a claude-code

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

GitHub CLI
$ gh skill install wshobson/agents startup-metrics-framework --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/wshobson/agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/startup-business-analyst/skills/startup-metrics-framework .claude/skills/startup-metrics-framework && 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
startup-metrics-framework
GitHub stars
40k
Token cost
~2.5k tokens
SKILL.md length
967 words
Files
1
Skills in repo
142
Repo updated
First seen
Licence
MIT

At a glance

Track, calculate, and optimize key performance metrics for SaaS, marketplace, consumer, and B2B startups from seed through Series A, including unit economics, growth efficiency, and cash management.

  • Works in 4 steps: Active users growth → User retention (Day 7, Day 30) → Core engagement (sessions, features used) → …
  • Defining a metrics framework
  • SKILL.md covers Overview, Universal Startup Metrics, SaaS Metrics and Marketplace Metrics, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Startup Metrics Framework is an agent skill from wshobson/agents. Track, calculate, and optimize key performance metrics for SaaS, marketplace, consumer, and B2B startups from seed through Series A, including unit economics, growth efficiency, and cash management. Use this skill when defining a metrics framework, calculating CAC/LTV/burn multiple, benchmarking business health, or preparing metrics dashboards for investors or board reporting.

Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Business, Finance & HR, covering Product metrics, Financial modeling and OKRs and executive reporting. The repository describes itself as: Multi-harness agentic plugin marketplace for Claude Code, Codex, Cursor, OpenCode, GitHub Copilot, Google Antigravity, and Pi. The licence is MIT.

When your agent uses it

  • Defining a metrics framework
  • Calculating CAC/LTV/burn multiple
  • Benchmarking business health
  • Preparing metrics dashboards for investors

Example prompts

  • “/startup-metrics-framework”

Workflow steps

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

  1. Active users growth
  2. User retention (Day 7, Day 30)
  3. Core engagement (sessions, features used)
  4. Qualitative feedback (NPS, interviews)

What it can do on your machine

Read from SKILL.md and the folder at commit 46891e7. 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

Startup Metrics Framework loads about 2.5k tokens when it runs. Until then it costs about 101 tokens; SKILL.md has 967 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~101
When it runs · the whole SKILL.md, loaded when a task matches
~2.5k

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 wshobson/agents at commit 46891e7, republished under its MIT licence (© wshobson). 967 words, ~2,507 tokens.

Download SKILL.mdSave it as .claude/skills/startup-metrics-framework/SKILL.md (or your agent's skills folder).
name
startup-metrics-framework
description
Track, calculate, and optimize key performance metrics for SaaS, marketplace, consumer, and B2B startups from seed through Series A, including unit economics, growth efficiency, and cash management. Use this skill when defining a metrics framework, calculating CAC/LTV/burn multiple, benchmarking business health, or preparing metrics dashboards for investors or board reporting.
version
1.0.0

Startup Metrics Framework

Comprehensive guide to tracking, calculating, and optimizing key performance metrics for different startup business models from seed through Series A.

Overview

Track the right metrics at the right stage. Focus on unit economics, growth efficiency, and cash management metrics that matter for fundraising and operational excellence.

Universal Startup Metrics

Revenue Metrics

MRR (Monthly Recurring Revenue)

MRR = Σ (Active Subscriptions × Monthly Price)

ARR (Annual Recurring Revenue)

ARR = MRR × 12

Growth Rate

MoM Growth = (This Month MRR - Last Month MRR) / Last Month MRR
YoY Growth = (This Year ARR - Last Year ARR) / Last Year ARR

Target Benchmarks:

  • Seed stage: 15-20% MoM growth
  • Series A: 10-15% MoM growth, 3-5x YoY
  • Series B+: 100%+ YoY (Rule of 40)
Unit Economics

CAC (Customer Acquisition Cost)

CAC = Total S&M Spend / New Customers Acquired

Include: Sales salaries, marketing spend, tools, overhead

LTV (Lifetime Value)

LTV = ARPU × Gross Margin% × (1 / Churn Rate)

Simplified:

LTV = ARPU × Average Customer Lifetime × Gross Margin%

LTV:CAC Ratio

LTV:CAC = LTV / CAC

Benchmarks:

  • LTV:CAC > 3.0 = Healthy
  • LTV:CAC 1.0-3.0 = Needs improvement
  • LTV:CAC < 1.0 = Unsustainable

CAC Payback Period

CAC Payback = CAC / (ARPU × Gross Margin%)

Benchmarks:

  • < 12 months = Excellent
  • 12-18 months = Good

  • 24 months = Concerning

Cash Efficiency Metrics

Burn Rate

Monthly Burn = Monthly Revenue - Monthly Expenses

Negative burn = losing money (typical early-stage)

Runway

Runway (months) = Cash Balance / Monthly Burn Rate

Target: Always maintain 12-18 months runway

Burn Multiple

Burn Multiple = Net Burn / Net New ARR

Benchmarks:

  • < 1.0 = Exceptional efficiency
  • 1.0-1.5 = Good
  • 1.5-2.0 = Acceptable

  • 2.0 = Inefficient

Lower is better (spending less to generate ARR)

SaaS Metrics

Revenue Composition

New MRR New customers × ARPU

Expansion MRR Upsells and cross-sells from existing customers

Contraction MRR Downgrades from existing customers

Churned MRR Lost customers

Net New MRR Formula:

Net New MRR = New MRR + Expansion MRR - Contraction MRR - Churned MRR
Retention Metrics

Logo Retention

Logo Retention = (Customers End - New Customers) / Customers Start

Dollar Retention (NDR - Net Dollar Retention)

NDR = (ARR Start + Expansion - Contraction - Churn) / ARR Start

Benchmarks:

  • NDR > 120% = Best-in-class
  • NDR 100-120% = Good
  • NDR < 100% = Needs work

Gross Retention

Gross Retention = (ARR Start - Churn - Contraction) / ARR Start

Benchmarks:

  • 90% = Excellent

  • 85-90% = Good
  • < 85% = Concerning
SaaS-Specific Metrics

Magic Number

Magic Number = Net New ARR (quarter) / S&M Spend (prior quarter)

Benchmarks:

  • 0.75 = Efficient, ready to scale

  • 0.5-0.75 = Moderate efficiency
  • < 0.5 = Inefficient, don't scale yet

Rule of 40

Rule of 40 = Revenue Growth Rate% + Profit Margin%

Benchmarks:

  • 40% = Excellent

  • 20-40% = Acceptable
  • < 20% = Needs improvement

Example: 50% growth + (10%) margin = 40% ✓

Quick Ratio

Quick Ratio = (New MRR + Expansion MRR) / (Churned MRR + Contraction MRR)

Benchmarks:

  • 4.0 = Healthy growth

  • 2.0-4.0 = Moderate
  • < 2.0 = Churn problem

Marketplace Metrics

GMV (Gross Merchandise Value)

Total Transaction Volume:

GMV = Σ (Transaction Value)

Growth Rate:

GMV Growth Rate = (Current Period GMV - Prior Period GMV) / Prior Period GMV

Target: 20%+ MoM early-stage

Take Rate
Take Rate = Net Revenue / GMV

Typical Ranges:

  • Payment processors: 2-3%
  • E-commerce marketplaces: 10-20%
  • Service marketplaces: 15-25%
  • High-value B2B: 5-15%
Marketplace Liquidity

Time to Transaction How long from listing to sale/match?

Fill Rate % of requests that result in transaction

Repeat Rate % of users who transact multiple times

Benchmarks:

  • Fill rate > 80% = Strong liquidity
  • Repeat rate > 60% = Strong retention
Marketplace Balance

Supply/Demand Ratio: Track relative growth of supply and demand sides.

Warning Signs:

  • Too much supply: Low fill rates, frustrated suppliers
  • Too much demand: Long wait times, frustrated customers

Goal: Balanced growth (1:1 ratio ideal, but varies by model)

Consumer/Mobile Metrics

Engagement Metrics

DAU (Daily Active Users) Unique users active each day

MAU (Monthly Active Users) Unique users active each month

DAU/MAU Ratio

DAU/MAU = DAU / MAU

Benchmarks:

  • 50% = Exceptional (daily habit)

  • 20-50% = Good
  • < 20% = Weak engagement

Session Frequency Average sessions per user per day/week

Session Duration Average time spent per session

Retention Curves

Day 1 Retention: % users who return next day Day 7 Retention: % users active 7 days after signup Day 30 Retention: % users active 30 days after signup

Benchmarks (Day 30):

  • 40% = Excellent

  • 25-40% = Good
  • < 25% = Weak

Retention Curve Shape:

  • Flattening curve = good (users becoming habitual)
  • Steep decline = poor product-market fit
Viral Coefficient (K-Factor)
K-Factor = Invites per User × Invite Conversion Rate

Example: 10 invites/user × 20% conversion = 2.0 K-factor

Benchmarks:

  • K > 1.0 = Viral growth
  • K = 0.5-1.0 = Strong referrals
  • K < 0.5 = Weak virality

B2B Metrics

Sales Efficiency

Win Rate

Win Rate = Deals Won / Total Opportunities

Target: 20-30% for new sales team, 30-40% mature

Sales Cycle Length Average days from opportunity to close

Shorter is better:

  • SMB: 30-60 days
  • Mid-market: 60-120 days
  • Enterprise: 120-270 days

Average Contract Value (ACV)

ACV = Total Contract Value / Contract Length (years)
Pipeline Metrics

Pipeline Coverage

Pipeline Coverage = Total Pipeline Value / Quota

Target: 3-5x coverage (3-5x pipeline needed to hit quota)

Conversion Rates by Stage:

  • Lead → Opportunity: 10-20%
  • Opportunity → Demo: 50-70%
  • Demo → Proposal: 30-50%
  • Proposal → Close: 20-40%

Metrics by Stage

Show full SKILL.md (391 more words)Show less
Pre-Seed (Product-Market Fit)

Focus Metrics:

  1. Active users growth
  2. User retention (Day 7, Day 30)
  3. Core engagement (sessions, features used)
  4. Qualitative feedback (NPS, interviews)

Don't worry about:

  • Revenue (may be zero)
  • CAC (not optimizing yet)
  • Unit economics
Seed ($500K-$2M ARR)

Focus Metrics:

  1. MRR growth rate (15-20% MoM)
  2. CAC and LTV (establish baseline)
  3. Gross retention (> 85%)
  4. Core product engagement

Start tracking:

  • Sales efficiency
  • Burn rate and runway
Series A ($2M-$10M ARR)

Focus Metrics:

  1. ARR growth (3-5x YoY)
  2. Unit economics (LTV:CAC > 3, payback < 18 months)
  3. Net dollar retention (> 100%)
  4. Burn multiple (< 2.0)
  5. Magic number (> 0.5)

Mature tracking:

  • Rule of 40
  • Sales efficiency
  • Pipeline coverage

Metric Tracking Best Practices

Data Infrastructure

Requirements:

  • Single source of truth (analytics platform)
  • Real-time or daily updates
  • Automated calculations
  • Historical tracking

Tools:

  • Mixpanel, Amplitude (product analytics)
  • ChartMogul, Baremetrics (SaaS metrics)
  • Looker, Tableau (BI dashboards)
Reporting Cadence

Daily:

  • MRR, active users
  • Sign-ups, conversions

Weekly:

  • Growth rates
  • Retention cohorts
  • Sales pipeline

Monthly:

  • Full metric suite
  • Board reporting
  • Investor updates

Quarterly:

  • Trend analysis
  • Benchmarking
  • Strategy review
Common Mistakes

Mistake 1: Vanity Metrics Don't focus on:

  • Total users (without retention)
  • Page views (without engagement)
  • Downloads (without activation)

Focus on actionable metrics tied to value.

Mistake 2: Too Many Metrics Track 5-7 core metrics intensely, not 50 loosely.

Mistake 3: Ignoring Unit Economics CAC and LTV are critical even at seed stage.

Mistake 4: Not Segmenting Break down metrics by customer segment, channel, cohort.

Mistake 5: Gaming Metrics Optimize for real business outcomes, not dashboard numbers.

Investor Metrics

What VCs Want to See

Seed Round:

  • MRR growth rate
  • User retention
  • Early unit economics
  • Product engagement

Series A:

  • ARR and growth rate
  • CAC payback < 18 months
  • LTV:CAC > 3.0
  • Net dollar retention > 100%
  • Burn multiple < 2.0

Series B+:

  • Rule of 40 > 40%
  • Efficient growth (magic number)
  • Path to profitability
  • Market leadership metrics
Metric Presentation

Dashboard Format:

Current MRR: $250K (↑ 18% MoM)
ARR: $3.0M (↑ 280% YoY)
CAC: $1,200 | LTV: $4,800 | LTV:CAC = 4.0x
NDR: 112% | Logo Retention: 92%
Burn: $180K/mo | Runway: 18 months

Include:

  • Current value
  • Growth rate or trend
  • Context (target, benchmark)

Quick Start

To implement startup metrics framework:

  1. Identify business model - SaaS, marketplace, consumer, B2B
  2. Choose 5-7 core metrics - Based on stage and model
  3. Establish tracking - Set up analytics and dashboards
  4. Calculate unit economics - CAC, LTV, payback
  5. Set targets - Use benchmarks for goals
  6. Review regularly - Weekly for core metrics
  7. Share with team - Align on goals and progress
  8. Update investors - Monthly/quarterly reporting

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

Files

Just SKILL.md in plugins/startup-business-analyst/skills/startup-metrics-framework of wshobson/agents.

Open the folder on GitHubat commit 46891e7

Compare with similar skills

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Categories

Questions about Startup Metrics Framework

What does Startup Metrics Framework do?

Track, calculate, and optimize key performance metrics for SaaS, marketplace, consumer, and B2B startups from seed through Series A, including unit economics, growth efficiency, and cash management. Startup Metrics Framework is an agent skill from wshobson/agents. Track, calculate, and optimize key performance metrics for SaaS, marketplace, consumer, and B2B startups from seed through Series A, including unit economics, growth efficiency, and cash management.

When should I use Startup Metrics Framework?

Startup Metrics Framework fits situations like: defining a metrics framework; calculating CAC/LTV/burn multiple; benchmarking business health; preparing metrics dashboards for investors.

How do I install Startup Metrics Framework in Claude Code?

Run `npx skills add wshobson/agents --skill startup-metrics-framework -a claude-code`. Or copy the skill folder (plugins/startup-business-analyst/skills/startup-metrics-framework in wshobson/agents) into .claude/skills/startup-metrics-framework in your project. Claude Code loads it when a task matches its description.

How do I install Startup Metrics Framework in Codex?

Run `npx skills add wshobson/agents --skill startup-metrics-framework -a codex`. Or copy the skill folder (plugins/startup-business-analyst/skills/startup-metrics-framework in wshobson/agents) into .agents/skills/startup-metrics-framework in your project. Codex loads it when a task matches its description.

Can I use Startup Metrics Framework 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 wshobson/agents --skill startup-metrics-framework -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/startup-metrics-framework, .gemini/skills/startup-metrics-framework, .github/skills/startup-metrics-framework and .opencode/skills/startup-metrics-framework in your project.

What does Startup Metrics Framework need to run?

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

Does Startup Metrics Framework 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 Startup Metrics Framework 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 Startup Metrics Framework use?

Startup Metrics Framework 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 Startup Metrics Framework use?

About 2.5k tokens (SKILL.md is roughly 10k 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 Startup Metrics Framework?

Skills that share tags, products or a category with Startup Metrics Framework: Startup Metrics Framework (aiskillstore/marketplace, 430 stars), Analytics Strategy (rampstackco/claude-skills, 941 stars), Goals And Kpis (social-media-skills/skills, 128 stars) and Kpi Framework (ericrisco/rsc-harness, 174 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Startup Metrics Framework?

wshobson (a GitHub user) maintains it in wshobson/agents, which has 40,305 GitHub stars. The repository holds 142 skills in this directory. The repository was last updated on October 5, 2026.

Source: wshobson/agents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.