Agent skill

Startup Metrics

by guia-matthieu in guia-matthieu/clawfu-skills

Know the metrics that matter at each stage and what investors actually look for.

MITAuto-check passedBusiness, Finance & HR

Install Startup Metrics

skills CLI
$ npx skills add guia-matthieu/clawfu-skills --skill startup-metrics -a claude-code

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

GitHub CLI
$ gh skill install guia-matthieu/clawfu-skills startup-metrics --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/guia-matthieu/clawfu-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/startup/startup-metrics .claude/skills/startup-metrics && 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
GitHub stars
150
Token cost
~5k tokens
SKILL.md length
1,236 words
Files
3 (incl. scripts)
Skills in repo
31
Repo updated
First seen
Licence
MIT

At a glance

Know the metrics that matter at each stage and what investors actually look for.

  • Works in 5 steps: Understand Metrics by Stage → Calculate Core SaaS Metrics → Benchmark Against Standards → …
  • : Fundraising prep to know which metrics to highlight
  • SKILL.md covers When to Use This Skill, Methodology Foundation, What Claude Does vs What You… and What This Skill Does, plus 5 more sections
  • Runs Python scripts from its folder

What it does

Startup Metrics is an agent skill from guia-matthieu/clawfu-skills. Know the metrics that matter at each stage and what investors actually look for. Master the A16Z and YC frameworks for measuring startup progress. Use when: Fundraising prep to know which metrics to highlight; Board meetings to report on the right KPIs; Strategic planning to set goals that matter; Product decisions to understand what to optimize; Diagnosing problems to find what's broken

Its SKILL.md is about 5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including scripts (for example `scripts/main.py`).

It sits in Business, Finance & HR, covering Startup and business strategy, Fundraising and pitch decks and OKRs and executive reporting. The repository describes itself as: 172 expert marketing skills for AI agents — ClawFu MCP Server. The licence is MIT.

When your agent uses it

  • : Fundraising prep to know which metrics to highlight
  • Board meetings to report on the right KPIs
  • Strategic planning to set goals that matter
  • Product decisions to understand what to optimize

Example prompts

  • “/startup-metrics”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Understand Metrics by Stage
  2. Calculate Core SaaS Metrics
  3. Benchmark Against Standards
  4. Diagnose Problems
  5. Create Investor Dashboard

What it can do on your machine

Read from SKILL.md and the folder at commit 4108f5c. 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

    Ships 2 files in scripts/ (Python), which the agent can run.

    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 loads about 5k tokens when it runs. Until then it costs about 107 tokens; SKILL.md has 1,236 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~107
When it runs · the whole SKILL.md, loaded when a task matches
~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); the scripts in this folder are not scanned.

SKILL.md

The full file from guia-matthieu/clawfu-skills at commit 4108f5c, republished under its MIT licence (© guia-matthieu). 1,236 words, ~4,961 tokens.

Download SKILL.mdSave it as .claude/skills/startup-metrics/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
startup-metrics
description
Know the metrics that matter at each stage and what investors actually look for. Master the A16Z and YC frameworks for measuring startup progress. Use when: **Fundraising prep** to know which metrics to highlight; **Board meetings** to report on the right KPIs; **Strategic planning** to set goals that matter; **Product decisions** to understand what to optimize; **Diagnosing problems** to find what's broken
license
MIT
metadata.author
ClawFu
metadata.version
1.0.0
metadata.mcp-server
@clawfu/mcp-skills

Startup Metrics

Know the metrics that matter at each stage and what investors actually look for. Master the A16Z and YC frameworks for measuring startup progress.

When to Use This Skill

  • Fundraising prep to know which metrics to highlight
  • Board meetings to report on the right KPIs
  • Strategic planning to set goals that matter
  • Product decisions to understand what to optimize
  • Diagnosing problems to find what's broken
  • Benchmarking to know if your metrics are good

Methodology Foundation

AspectDetails
SourceA16Z (Andreessen Horowitz), YC (Y Combinator), SaaS metrics best practices
Core Principle"Measure what matters. Vanity metrics feel good but don't predict success. Focus on metrics that indicate real product-market fit and sustainable growth."
Why This MattersWrong metrics lead to wrong decisions. Right metrics reveal truth about your business—good or bad—before it's too late to course-correct.

What Claude Does vs What You Decide

Claude DoesYou Decide
Structures analysis frameworksStrategic priorities
Synthesizes market dataCompetitive positioning
Identifies opportunitiesResource allocation
Creates strategic optionsFinal strategy selection
Suggests implementation approachesExecution decisions

What This Skill Does

  1. Identifies key metrics by stage - What to measure when
  2. Calculates core SaaS metrics - ARR, MRR, churn, LTV, CAC
  3. Benchmarks performance - Good vs. great vs. concerning
  4. Diagnoses metric problems - What poor metrics indicate
  5. Prepares investor-ready dashboards - What VCs want to see
  6. Prioritizes metric improvement - What to fix first

How to Use

Get Stage-Appropriate Metrics
I'm a [stage] startup in [industry].
What metrics should I be tracking?
What benchmarks should I aim for?
Calculate Core Metrics
Help me calculate my SaaS metrics:
[Provide: MRR, customer count, churn data, acquisition costs]
Diagnose Metric Problems
My metrics: [list metrics]
What's concerning? What should I focus on fixing?

Instructions

Step 1: Understand Metrics by Stage
## Metrics Framework by Stage

### Pre-Seed (Validation Stage)
**Focus:** Is this a real problem worth solving?

| Metric | Why It Matters | Good Signal |
|--------|---------------|-------------|
| Problem interviews | Validate problem exists | 10+ interviews, 70%+ confirm |
| Solution interviews | Validate solution fits | 60%+ would use |
| LOIs/Waitlist | Real interest signal | Signed commitments |
| Engagement (if prototype) | People want to use it | Daily active usage |

**Not important yet:** Revenue, CAC, LTV, growth rate

---

### Seed (Product-Market Fit Stage)
**Focus:** Do people want this? Will they pay?

| Metric | Why It Matters | Good Signal |
|--------|---------------|-------------|
| **MRR/ARR** | Revenue traction | Any consistent revenue |
| **MoM Growth** | Trajectory | 15-20%+ MoM |
| **Retention** | PMF indicator | >80% monthly retention |
| **NPS** | Customer love | >50 NPS |
| **Engagement** | Product usage | DAU/MAU >20% |

**Emerging importance:** Early unit economics, CAC/LTV ratio

---

### Series A (Scale Stage)
**Focus:** Can this scale? Are unit economics viable?

| Metric | Why It Matters | Good Signal |
|--------|---------------|-------------|
| **ARR** | Revenue scale | $1-2M+ |
| **ARR Growth** | YoY trajectory | 3x YoY |
| **Net Revenue Retention** | Expansion + churn | >100% (ideally >120%) |
| **LTV/CAC** | Unit economics | >3:1 |
| **CAC Payback** | Efficiency | <18 months |
| **Gross Margin** | Business viability | >70% (SaaS) |

---

### Series B+ (Optimization Stage)
**Focus:** Efficiency and path to profitability

| Metric | Why It Matters | Good Signal |
|--------|---------------|-------------|
| **Magic Number** | Sales efficiency | >0.75 |
| **Rule of 40** | Growth + profitability | >40% |
| **Burn Multiple** | Cash efficiency | <2x |
| **Net Dollar Retention** | Account growth | >120% |
| **Quick Ratio** | Growth quality | >4 |

Step 2: Calculate Core SaaS Metrics
## Metric Calculations

### Revenue Metrics

**MRR (Monthly Recurring Revenue):**
MRR = Sum of all recurring revenue per month

**ARR (Annual Recurring Revenue):**
ARR = MRR × 12

**MRR Components:**
- New MRR: Revenue from new customers
- Expansion MRR: Upgrades and cross-sells
- Contraction MRR: Downgrades
- Churned MRR: Lost customers

**Net New MRR:**
Net New MRR = New + Expansion - Contraction - Churned

---

### Growth Metrics

**MoM Growth Rate:**
Growth = (MRR this month - MRR last month) / MRR last month × 100

**YoY Growth Rate:**
YoY = (ARR this year - ARR last year) / ARR last year × 100

**CMGR (Compound Monthly Growth Rate):**
CMGR = (Ending MRR / Starting MRR)^(1/months) - 1

---

### Retention Metrics

**Gross Revenue Retention (GRR):**
GRR = (MRR - Churned MRR - Contraction MRR) / MRR × 100
Maximum: 100% (doesn't include expansion)

**Net Revenue Retention (NRR) / Net Dollar Retention (NDR):**
NRR = (MRR + Expansion - Contraction - Churned) / MRR × 100
Can be >100% (good!)

**Logo Churn:**
Logo Churn = Customers lost / Customers at start of period × 100

**Revenue Churn:**
Revenue Churn = Churned MRR / MRR at start of period × 100

---

### Unit Economics

**Customer Acquisition Cost (CAC):**
CAC = Total Sales & Marketing Spend / New Customers Acquired

**Lifetime Value (LTV):**
Simple: LTV = ARPU × Gross Margin × Customer Lifetime
With churn: LTV = (ARPU × Gross Margin) / Monthly Churn Rate

**LTV/CAC Ratio:**
LTV/CAC = LTV / CAC
Good: >3:1

**CAC Payback Period:**
Payback = CAC / (ARPU × Gross Margin)
Good: <18 months

---

### Efficiency Metrics

**Magic Number:**
Magic Number = Net New ARR this quarter / S&M Spend last quarter
>1.0 = Very efficient
0.75-1.0 = Good
<0.5 = Inefficient

**Rule of 40:**
Rule of 40 = Revenue Growth Rate + Profit Margin
>40% = Healthy balance of growth and profitability

**Burn Multiple:**
Burn Multiple = Net Burn / Net New ARR
<1x = Excellent
1-2x = Good
>2x = Concerning

**Quick Ratio:**
Quick Ratio = (New MRR + Expansion MRR) / (Churned MRR + Contraction MRR)
>4 = Excellent growth quality

Step 3: Benchmark Against Standards
## Metric Benchmarks

### SaaS Benchmarks by Stage

| Metric | Seed | Series A | Series B |
|--------|------|----------|----------|
| ARR | <$1M | $1-5M | $5-15M |
| MoM Growth | 15-25% | 10-15% | 5-10% |
| YoY Growth | 3x+ | 2-3x | 1.5-2x |
| Gross Margin | >60% | >70% | >75% |
| LTV/CAC | >3x | >3x | >4x |
| CAC Payback | <24 mo | <18 mo | <12 mo |
| NRR | >100% | >110% | >120% |
| Logo Churn | <5%/mo | <3%/mo | <2%/mo |

### What "Good" Looks Like by Company Type

**SMB SaaS (low touch):**
- Logo churn: 3-5% monthly
- NRR: 80-100%
- LTV/CAC: >3x
- CAC: <$1,000

**Mid-Market SaaS:**
- Logo churn: 1-2% monthly
- NRR: 100-120%
- LTV/CAC: >4x
- CAC: $5,000-20,000

**Enterprise SaaS:**
- Logo churn: <1% monthly
- NRR: 110-150%
- LTV/CAC: >5x
- CAC: $20,000-100,000+

### Engagement Benchmarks

| Metric | Consumer | B2B SaaS |
|--------|----------|----------|
| DAU/MAU | >20% | >40% |
| D1 Retention | >40% | >50% |
| D7 Retention | >20% | >30% |
| D30 Retention | >10% | >20% |

Step 4: Diagnose Problems
## Metric Diagnosis Guide

### If MRR Growth is Slowing...

**Possible causes:**
1. Market saturation (ran out of easy customers)
2. Product-market fit weakening (competition, changing needs)
3. Sales inefficiency (declining magic number)
4. High churn eating new growth

**Diagnostic questions:**
- Is logo churn increasing?
- Is CAC increasing?
- Is conversion rate declining?
- Is expansion revenue flat?

---

### If Churn is High...

**Possible causes:**
1. Onboarding problems (never got value)
2. Product gaps (missing critical features)
3. Wrong customers (sold to people who shouldn't buy)
4. Competition (better alternatives emerged)
5. Pricing mismatch (not worth it)

**Diagnostic questions:**
- When do customers churn? (early = onboarding, late = value)
- What's the churn reason? (survey departures)
- Which segments churn most?
- What's usage pattern before churn?

---

### If CAC is Too High...

**Possible causes:**
1. Wrong channel (expensive acquisition)
2. Poor targeting (low conversion)
3. Weak positioning (hard to differentiate)
4. Long sales cycles (expensive process)
5. Market competition (bidding up costs)

**Diagnostic questions:**
- What's CAC by channel?
- What's conversion rate at each stage?
- How long is sales cycle?
- What's win rate vs. competition?

---

### If LTV is Too Low...

**Possible causes:**
1. High churn (short lifetime)
2. Low ARPU (underpriced or wrong segment)
3. No expansion revenue (no upsell path)
4. Low gross margin (cost too high)

**Diagnostic questions:**
- What's average customer lifespan?
- What's ARPU distribution?
- What's expansion revenue %?
- Are costs scaling with revenue?

---

### Quick Diagnostic Table

| Symptom | Primary Metric | Secondary Checks |
|---------|---------------|------------------|
| Revenue plateau | MRR growth rate | New vs. expansion breakdown |
| Customers leaving | Churn rate | Cohort analysis, exit surveys |
| Expensive growth | CAC, Magic Number | Channel efficiency, conversion |
| Low profitability | Gross margin | COGS breakdown, pricing |
| "Leaky bucket" | Quick Ratio | Churn + expansion balance |

Step 5: Create Investor Dashboard
## Investor Metrics Dashboard

### What Investors Want to See (by stage)

**Seed Deck Metrics:**
- MRR and growth trajectory
- Customer count and retention
- Engagement metrics
- Early unit economics (if available)

**Series A Deck Metrics:**
- ARR and YoY growth
- Net Revenue Retention
- LTV/CAC ratio
- CAC Payback
- Cohort analysis
- Customer breakdown by segment

**Series B+ Deck Metrics:**
All of above plus:
- Magic Number
- Rule of 40
- Burn Multiple
- Detailed unit economics by segment
- Efficiency trends over time

### Dashboard Template

[Company] Metrics Dashboard

As of [Date]
Revenue
  • ARR: $[X]
  • MRR: $[X]
  • MoM Growth: [X]%
  • YoY Growth: [X]%
Customers
  • Total Customers: [X]
  • New This Month: [X]
  • Churned This Month: [X]
  • Logo Churn Rate: [X]%
Retention
  • Gross Revenue Retention: [X]%
  • Net Revenue Retention: [X]%
  • Average Customer Lifespan: [X] months
Unit Economics
  • ARPU: $[X]
  • CAC: $[X]
  • LTV: $[X]
  • LTV/CAC: [X]:1
  • Payback: [X] months
Efficiency
  • Gross Margin: [X]%
  • Magic Number: [X]
  • Burn Multiple: [X]
Engagement
  • DAU: [X]
  • DAU/MAU: [X]%
  • Feature adoption: [X]%

Examples

Example 1: Seed Stage Metrics Analysis

Input:

"I'm raising Seed. Here are my metrics. How do they look?" MRR: $15K, 6 months old, 40 customers MoM growth: 20% average Churn: 5% monthly CAC: $200

Output:

Metrics Analysis: Seed Stage

Current State
MetricValueBenchmarkAssessment
MRR$15K-Early but positive
MoM Growth20%15-25%✅ Good
Customer Count40-Reasonable for stage
Monthly Churn5%<5%⚠️ At threshold
CAC$200<$500 SMB✅ Efficient
Calculated Metrics

ARPU: $15,000 / 40 = $375/month

Implied LTV (simple):

  • Customer lifespan: 1 / 0.05 = 20 months
  • LTV = $375 × 20 = $7,500

LTV/CAC: $7,500 / $200 = 37.5:1 ✅ Excellent

CAC Payback: $200 / $375 = 0.5 months ✅ Excellent

Analysis

Strengths:

  • Growth rate is healthy (20% MoM = 8.9x annual)
  • CAC is very efficient
  • LTV/CAC is strong (though churn may be early-stage noise)

Concerns:

  • 5% monthly churn = 60% annual churn (high for SaaS)
  • Small sample size (40 customers)
  • Need to see cohort retention to understand true churn

Questions to Answer:

  1. Is 5% churn consistent across cohorts or improving?
  2. What's the activation rate? (Are churners ever getting value?)
  3. What's usage pattern of retained customers?
Investor Readiness

For Seed, you need to show:

  • ✅ Growth trajectory (20% MoM is good)
  • ✅ Efficient acquisition
  • ⚠️ Retention story (need cohort data)
  • ❓ Path to scale

Recommendation:

  • Highlight growth and CAC efficiency
  • Show cohort data if recent cohorts retain better
  • Explain what you're doing to improve retention
  • Project what metrics look like with improved retention
Projected Growth
MetricNow+6 months (at 20% MoM)+12 months
MRR$15K$45K$133K
ARR$180K$540K$1.6M
Customers40~100~250

Example 2: Diagnose Declining Growth

Input:

"My MoM growth dropped from 25% to 8% over 4 months. What's happening?"

Output:

Growth Decline Diagnosis

Data Needed
Metric4 months agoNowChange
New MRR??
Expansion MRR??
Churned MRR??
Logo Churn??
New Customers??
Sales Pipeline??
CAC??
Conversion Rate??
Diagnostic Framework

Question 1: Is this a LEAKY BUCKET problem?

  • Are you acquiring the same # of customers but losing more?
  • Check: New MRR vs. Churned MRR

Question 2: Is this an ACQUISITION problem?

  • Are you getting fewer new customers?
  • Check: New customer count, pipeline, conversion rate

Question 3: Is this an EXPANSION problem?

  • Has expansion revenue slowed?
  • Check: Expansion MRR trend, upsell rate
Show full SKILL.md (524 more words)Show less
Common Scenarios

Scenario A: Churn increased Symptoms: New MRR stable, but churned MRR grew Causes: Product issues, wrong customers, competition Fix: Churn analysis, customer success, product fixes

Scenario B: New acquisition slowed Symptoms: Churned MRR stable, but new MRR decreased Causes: Market saturation, CAC increased, marketing efficiency dropped Fix: New channels, positioning, sales optimization

Scenario C: Expansion stalled Symptoms: New + churn stable, but expansion dropped Causes: Product limits hit, no upsell path, customer saturation Fix: New features, pricing tiers, account management

Scenario D: Multiple factors Often it's a combination—growth hides problems until it slows

Investigation Checklist
□ Break down MRR: New, Expansion, Contraction, Churned
□ Compare ratios: Quick Ratio trend
□ Cohort analysis: Are newer cohorts worse?
□ Channel breakdown: Which channels slowed?
□ Segment analysis: Which customer type slowed?
□ Funnel metrics: Where is conversion dropping?
□ Win/loss analysis: Why are deals not closing?
□ Churn interviews: Why are customers leaving?
Next Steps
  1. Get the data breakdown (above table)
  2. Identify primary driver (acquisition, churn, or expansion)
  3. Root cause analysis on that driver
  4. Hypothesis and test solutions
  5. Monitor leading indicators weekly

Example 3: Series A Readiness Check

Input:

"Am I ready for Series A? ARR: $1.2M, NRR: 108%, LTV/CAC: 4.5x, YoY growth: 180%"

Output:

Series A Readiness Assessment

Metrics Scorecard
MetricYour ValueSeries A BarStatus
ARR$1.2M$1-2M✅ Pass
YoY Growth180%100-200%✅ Strong
NRR108%>100%✅ Pass
LTV/CAC4.5x>3x✅ Strong
What You Have

✅ Revenue scale: $1.2M ARR is at the low end of Series A but acceptable with strong growth ✅ Growth rate: 180% YoY is excellent (shows demand) ✅ Retention: 108% NRR means customers expand (PMF signal) ✅ Unit economics: 4.5x LTV/CAC is healthy

What Investors Will Ask

You'll need answers to:

  1. CAC Payback? (Need to calculate)
  2. Gross Margin? (Should be >70% for SaaS)
  3. Logo vs. Revenue Churn? (Both matter)
  4. Cohort data? (Do later cohorts retain better?)
  5. Segmentation? (Which customer type is best?)
  6. Magic Number? (Sales efficiency)
  7. Path to $10M ARR? (How do you 8x?)
Additional Metrics Needed
MetricRequiredNice to Have
CAC Payback✅ Yes
Gross Margin✅ Yes
MoM Growth Trend✅ Yes
Customer Count✅ Yes
Cohort Retention✅ Yes
Magic Number✅
Burn Multiple✅
ACV Distribution✅
Series A Narrative

Based on your metrics, your story is:

"We've found product-market fit in [segment]. $1.2M ARR growing 180% YoY with 108% NRR proves customers want this and expand. Our 4.5x LTV/CAC shows we can acquire customers profitably. With Series A, we'll [go-to-market strategy] to reach $5M ARR in 18 months."

Recommendations
  1. Strengthen weak spots before raising:

    • Calculate and optimize CAC Payback
    • Document gross margin
    • Build cohort analysis
  2. Prepare growth story:

    • What drives growth? (channels, segments)
    • Why will this continue?
    • What does $10M ARR look like?
  3. Document efficiency:

    • Magic Number (if positive)
    • Burn Multiple (if reasonable)

Verdict: You're in the range for Series A. Focus on the narrative and missing metrics before starting outreach.


Checklists & Templates

Metrics Tracking Checklist
## Monthly Metrics Review

### Revenue
□ MRR calculated (New + Expansion - Contraction - Churned)
□ ARR updated
□ MoM growth rate
□ YoY comparison (if applicable)

### Customers
□ Customer count
□ New customers
□ Churned customers
□ Logo churn rate

### Retention
□ Gross Revenue Retention
□ Net Revenue Retention
□ Cohort retention updated

### Unit Economics
□ CAC (by channel if possible)
□ LTV updated
□ LTV/CAC ratio
□ Payback period

### Engagement
□ DAU/MAU
□ Feature adoption
□ Key usage metrics

### Efficiency (Series A+)
□ Magic Number
□ Burn Multiple
□ Rule of 40

Skill Boundaries

What This Skill Does Well
  • Structuring strategic analysis
  • Identifying market opportunities
  • Creating strategic frameworks
  • Synthesizing competitive data
What This Skill Cannot Do
  • Replace market research
  • Guarantee strategic success
  • Know proprietary competitor info
  • Make executive decisions

References

  • A16Z. "16 Startup Metrics" (Andreessen Horowitz)
  • YC. "Startup Metrics That Matter" (Y Combinator)
  • Tunguz, Tomasz. "SaaS Metrics" (Redpoint Ventures)
  • Reforge. "Retention Curves" & "Growth Accounting"
  • OpenView Partners. "SaaS Benchmarks"

Skill Metadata

  • Mode: centaur
yaml
name: startup-metrics
category: startup
subcategory: measurement
version: 1.0
author: MKTG Skills
source_expert: A16Z, YC, SaaS Metrics Community
source_work: 16 Startup Metrics, YC Library
difficulty: intermediate
estimated_value: $5,000 financial modeling consulting
tags: [metrics, SaaS, startup, fundraising, KPIs, A16Z, YC]
created: 2026-01-25
updated: 2026-01-25

© guia-matthieu, 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 2 other files (scripts) in skills/startup/startup-metrics of guia-matthieu/clawfu-skills.

  • SKILL.md
  • scripts/main.py
  • scripts/requirements.txt

Open the folder on GitHubat commit 4108f5c

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Board Deck Builderalirezarezvani/claude-skills28k1 repos~1.9kAutomated safety check: PassMIT

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Questions about Startup Metrics

What does Startup Metrics do?

Know the metrics that matter at each stage and what investors actually look for. Startup Metrics is an agent skill from guia-matthieu/clawfu-skills. Know the metrics that matter at each stage and what investors actually look for.

When should I use Startup Metrics?

Startup Metrics fits situations like: : Fundraising prep to know which metrics to highlight; board meetings to report on the right KPIs; strategic planning to set goals that matter; product decisions to understand what to optimize.

How do I install Startup Metrics in Claude Code?

Run `npx skills add guia-matthieu/clawfu-skills --skill startup-metrics -a claude-code`. Or copy the skill folder (skills/startup/startup-metrics in guia-matthieu/clawfu-skills) into .claude/skills/startup-metrics in your project. Claude Code loads it when a task matches its description.

How do I install Startup Metrics in Codex?

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

Can I use Startup Metrics 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 guia-matthieu/clawfu-skills --skill startup-metrics -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, .gemini/skills/startup-metrics, .github/skills/startup-metrics and .opencode/skills/startup-metrics in your project.

What does Startup Metrics need to run?

Going by SKILL.md and its folder, Startup Metrics needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Startup Metrics 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 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Startup Metrics use?

Startup Metrics is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Startup Metrics use?

About 5k tokens (SKILL.md is roughly 20k 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?

Skills that share tags, products or a category with Startup Metrics: Replit Deck (sanqiufong/slides-from-anything, 132 stars), Board Update (shawnpang/startup-founder-skills, 343 stars), Product Strategist (davila7/claude-code-templates, 33k stars) and Gtm Board And Investor Communication (github/awesome-copilot, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Startup Metrics?

guia-matthieu (a GitHub user) maintains it in guia-matthieu/clawfu-skills, which has 150 GitHub stars. The repository holds 31 skills in this directory. The repository was last updated on October 1, 2026.

Source: guia-matthieu/clawfu-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.