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metric-framework-designer

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업데이트2026년 7월 2일 17:22

Define the measurement framework BEFORE launch. North star, activation criterion, retention targets, Sean Ellis target, and false-positive shape.

설치

Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.

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hamza-ali-shahjahan

hamza-ali-shahjahan/hamzaish

GitHub 저장소 열기 Creator 저장소 보기

다운로드

Manus에서 실행

Metric Framework Designer

When you activate

Before a product's first real user. User says: "what should I track?", "set up metrics for X", "ready to launch — what do I measure?"

What you produce

A products/<name>/metrics.md file:

## Metrics Framework — <product>

### North star metric
<single number> — what we optimize for above all else.
Why this one: <reasoning>

### Activation criterion
A user is "activated" when they: <specific action within Y minutes/days of signup>.
Why this defines "real" use: <reasoning>

### Retention targets
- Day 1: ≥ X% of activated users return
- Day 7: ≥ Y%
- Day 30: ≥ Z%
- Benchmarks based on <industry / similar-product reference>

### PMF target
Sean Ellis survey at N=40 active users: ≥40% answer "very disappointed" to "how would you feel if you could no longer use this?"

### False-positive shape (what would LOOK like PMF but isn't?)
1. <e.g. "spike from HN front page that decays in 7 days">
2. <e.g. "high signup rate but D7 retention < 20%">
3. <e.g. "founder's network signup dominance">

### Anti-metrics (things we deliberately don't optimize)
- <e.g. "page views" — vanity>
- <e.g. "signups without activation" — see above>

### Reporting cadence
- Daily: 1 number — yesterday's <NSM>
- Weekly: cohort retention curve + signup → activation funnel
- Monthly: revenue, churn, expansion (post-payments)

### Tracking implementation
- PostHog events to fire: <list of event names>
- PostHog dashboards to create: <list>
- GSC + Plausible: <what to watch>

Protocol

Read the product's scope.md and prd.md — what value does this product deliver?
Pick the north-star metric that most cleanly proxies "is the product delivering value?" Not "is it growing?" — that's a derivative.
Define activation precisely. A user who signed up isn't activated. Activation is the moment they got value.
Set retention benchmarks. Pull from factory/playbooks/mvp-stage/measurement-framework.md for indie benchmarks by product type (SaaS, marketplace, content, tool).
Set the Sean Ellis target. Reference factory/playbooks/mvp-stage/sean-ellis-survey.md.
List 3 false-positive shapes that are specific to this product's dynamics.
List anti-metrics. Forcing this list reduces vanity-metric drift.
Write the PostHog event names that need firing — pass to mvp/builder as a task.

Sources

factory/playbooks/mvp-stage/measurement-framework.md
factory/playbooks/mvp-stage/sean-ellis-survey.md
factory/playbooks/scale-stage/growth-loops-reforge.md (for understanding retention curves)

What you don't do

Don't pick a north-star metric that's just a count. NSMs are usually combinations or rates.
Don't set targets without a referenced benchmark.
Don't skip the false-positive section — that's the whole point of measuring before launch.

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Metric Framework Designer

When you activate

Before a product's first real user. User says: "what should I track?", "set up metrics for X", "ready to launch — what do I measure?"

What you produce

A products/<name>/metrics.md file:

## Metrics Framework — <product> ### North star metric <single number> — what we optimize for above all else. Why this one: <reasoning> ### Activation criterion A user is "activated" when they: <specific action within Y minutes/days of signup>. Why this defines "real" use: <reasoning> ### Retention targets - Day 1: ≥ X% of activated users return - Day 7: ≥ Y% - Day 30: ≥ Z% - Benchmarks based on <industry / similar-product reference> ### PMF target Sean Ellis survey at N=40 active users: ≥40% answer "very disappointed" to "how would you feel if you could no longer use this?" ### False-positive shape (what would LOOK like PMF but isn't?) 1. <e.g. "spike from HN front page that decays in 7 days"> 2. <e.g. "high signup rate but D7 retention < 20%"> 3. <e.g. "founder's network signup dominance"> ### Anti-metrics (things we deliberately don't optimize) - <e.g. "page views" — vanity> - <e.g. "signups without activation" — see above> ### Reporting cadence - Daily: 1 number — yesterday's <NSM> - Weekly: cohort retention curve + signup → activation funnel - Monthly: revenue, churn, expansion (post-payments) ### Tracking implementation - PostHog events to fire: <list of event names> - PostHog dashboards to create: <list> - GSC + Plausible: <what to watch>

Protocol

Read the product's scope.md and prd.md — what value does this product deliver?

Pick the north-star metric that most cleanly proxies "is the product delivering value?" Not "is it growing?" — that's a derivative.

Define activation precisely. A user who signed up isn't activated. Activation is the moment they got value.

Set retention benchmarks. Pull from factory/playbooks/mvp-stage/measurement-framework.md for indie benchmarks by product type (SaaS, marketplace, content, tool).

Set the Sean Ellis target. Reference factory/playbooks/mvp-stage/sean-ellis-survey.md.

List 3 false-positive shapes that are specific to this product's dynamics.

List anti-metrics. Forcing this list reduces vanity-metric drift.

Write the PostHog event names that need firing — pass to mvp/builder as a task.

Sources

factory/playbooks/mvp-stage/measurement-framework.md

factory/playbooks/mvp-stage/sean-ellis-survey.md

factory/playbooks/scale-stage/growth-loops-reforge.md (for understanding retention curves)

What you don't do

Don't pick a north-star metric that's just a count. NSMs are usually combinations or rates.

Don't set targets without a referenced benchmark.

Don't skip the false-positive section — that's the whole point of measuring before launch.

name	metric-framework-designer
description	Define the measurement framework BEFORE launch. North star, activation criterion, retention targets, Sean Ellis target, and false-positive shape.
model_tier	sonnet