How Input Metrics Are Calculated for the North Star Metric Skill in pm-skills

Input metrics for the North Star Metric skill are determined through a structured 4-step process that classifies the business game, generates NSM candidates, selects the optimal metric, and defines 3-5 MECE (mutually exclusive, collectively exhaustive) leading indicators that directly drive the NSM, with each input containing causal links, ownership, current values, and targets.

The phuryn/pm-skills repository provides a structured framework for product teams to define their North Star Metric and its supporting input metrics. Understanding how input metrics are calculated for the North Star Metric skill requires examining the skill definition in pm-marketing-growth/skills/north-star-metric/SKILL.md and its command wrapper implementation. This open-source skill system helps product managers establish MECE leading indicators that drive business success.

Understanding the North Star Metric Skill Framework

The North Star Metric (NSM) skill resides in the pm-marketing-growth package and helps teams identify a single customer-centric KPI that drives business success. According to the skill definition in pm-marketing-growth/skills/north-star-metric/SKILL.md, the framework requires identifying one NSM supported by 3-5 input metrics that function as actionable leading indicators.

The skill leverages the shared data model from pm-product-discovery/skills/metrics-dashboard/SKILL.md to ensure consistency across product discovery and growth teams. This integration ensures that input metrics align with broader metrics dashboard standards for health metrics and alerts.

The Input Metrics Calculation Process

The calculation of input metrics follows a four-step workflow defined in the command wrapper at pm-marketing-growth/commands/north-star.md.

Step 1: Classify the Business Game

First, the skill classifies the product's business game into one of three categories:

• Attention – Products where primary value is user engagement
• Transaction – Platforms focused on commerce or exchange
• Productivity – Tools that emphasize output efficiency

This classification determines which types of metrics are appropriate for the specific product context.

Step 2: Generate NSM Candidates

The system generates 2-3 candidate metrics and evaluates them against seven criteria for an effective North Star Metric. These criteria ensure the metric captures core value delivered to users and serves as a leading indicator rather than a vanity metric such as raw revenue.

Step 3: Select the North Star Metric

After evaluation against the seven criteria, the team selects the optimal NSM that best represents the product's core value proposition. The selected metric must capture the core value the product delivers to its users, such as "daily active users who complete a value-adding action."

Step 4: Define Input Metrics with MECE Principles

Finally, the skill calculates specific input metrics by identifying 3-5 "lever" metrics that directly drive the NSM. As defined in pm-product-discovery/skills/metrics-dashboard/SKILL.md, these inputs must be MECE (mutually exclusive, collectively exhaustive). Each input metric requires:

1. Causal link description – How the metric drives the NSM
2. Owner – Team or individual responsible
3. Current value – Baseline measurement
4. Target – Desired future state

Technical Implementation in pm-skills

The skill implementation relies on three key files. The SKILL.md manifest at pm-marketing-growth/skills/north-star-metric/SKILL.md declares trigger phrases like "north star metric" and "define north star" along with the step-by-step workflow. The command wrapper at pm-marketing-growth/commands/north-star.md exposes the skill via the /north-star CLI command used by the Claude plugin system.

The framework reuses the metrics dashboard data model from pm-product-discovery/skills/metrics-dashboard/SKILL.md to ensure consistency across teams. This shared model defines the structure for NSM, input metrics, health metrics, and alerts.

Code Examples

Users invoke the skill through the /north-star command. The following example demonstrates the input metrics calculation output:

/north-star

> I'm going to help you pick a North Star Metric and three supporting input metrics.
> 1️⃣ **Classify the business game** – Are you building an attention-driven app, a transaction platform, or a productivity tool?
> 2️⃣ **NSM candidates** – e.g., "Weekly active creators", "Monthly revenue-per-user", "Time saved per session".
> 3️⃣ **Select the NSM** – "Weekly active creators" (captures value delivered to creators).
> 4️⃣ **Input metrics**  
> | Input Metric | Drives NSM By | Owner | Current | Target |  
> |--------------|--------------|-------|---------|--------|  
> | New creator sign-ups | ↑ weekly active creators | Growth | 1,200 /mo | 1,800 /mo |  
> | Creator content uploads | ↑ weekly active creators | Product | 3,000 /mo | 4,500 /mo |  
> | Retention (30-day) | ↑ weekly active creators | Ops | 45% | 55% |

When running the specific input-metrics step, the skill provides detailed causal explanations:

/north-star input-metrics

> Based on the selected NSM "Weekly active creators", here are three actionable input metrics:
> • **New creator sign-ups** – the funnel entry point; increase acquisition spend.
> • **Creator content uploads** – the amount of value creators add; improve onboarding flow.
> • **30-day retention** – keeps creators engaged; refine product-led growth loops.

Summary

• Input metrics are calculated through a 4-step process defined in pm-marketing-growth/commands/north-star.md.
• The framework requires 3-5 input metrics that follow MECE principles (mutually exclusive, collectively exhaustive).
• Each input metric must include causal links to the NSM, ownership, current values, and targets.
• The implementation leverages the shared metrics dashboard model from pm-product-discovery/skills/metrics-dashboard/SKILL.md.
• Business game classification (Attention, Transaction, Productivity) determines the appropriate metric types.

Frequently Asked Questions

What does MECE mean in the context of input metrics?

MECE stands for Mutually Exclusive, Collectively Exhaustive. In the North Star Metric skill, this principle ensures that the 3-5 input metrics do not overlap in scope (mutually exclusive) while collectively covering all possible drivers of the NSM (collectively exhaustive). This prevents double-counting and ensures comprehensive coverage of value drivers as required by the skill definition.

How many input metrics should be defined for a North Star Metric?

The skill requires exactly 3-5 input metrics for each North Star Metric. This constraint ensures focus on the most critical levers while maintaining manageable complexity for the product team. According to pm-marketing-growth/skills/north-star-metric/SKILL.md, fewer than three may miss critical drivers, while more than five becomes unwieldy for execution.

What is the difference between the NSM and input metrics?

The North Star Metric is a single leading indicator that captures the core value delivered to users, such as "Weekly active creators." Input metrics are the actionable leading indicators that directly drive changes in the NSM, such as "New creator sign-ups" or "30-day retention." While the NSM measures value delivered, input metrics measure the specific actions or conditions that create that value.

How are input metrics validated in the framework?

The validation process ensures inputs are MECE and that each metric has a clear causal link to the NSM. As implemented in pm-marketing-growth/skills/north-star-metric/SKILL.md, the skill checks that input metrics are concrete, actionable, and owned by specific team members, with documented current values and targets.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}