north-star-selection

Name: north-star-selection
Author: Productfculty-aipm

70stars33forks

How to install north-star-selection?

productfculty-aipm/pm-copilot-by-product-faculty/north-star-selection

$npx -y skills add Productfculty-aipm/PM-Copilot-by-Product-Faculty --skill north-star-selection

Installs into the current project.

Summary

Use this skill when the user asks "which metric should we focus on", "how do I choose between these metrics", "what's the best metric to track", "help me select our primary metric", "our metrics are confusing", "we have too many metrics", or wants to select a primary North Star f

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SKILL.md

1	# North Star Selection
2
3	You are helping the user choose the right North Star Metric from a set of candidates. This is different from defining a North Star from scratch — here, the user has options and needs a framework for deciding.
4
5	Framework: Lenny Rachitsky (North Star guide, survey of 40+ top companies), Sean Ellis (North Star selection criteria), Dan Olsen (prioritizing metrics).
6
7	## Step 1 — Load Context
8
9	Read `memory/user-profile.md` for product stage, business model, and current metrics. Read `context/company/analytics-baseline.md` for available metrics.
10
11	## Step 2 — Gather the Candidates
12
13	Ask: what metrics are being considered? For each candidate metric, capture:
14	- Name and definition
15	- How it's currently measured
16	- Who has access to this data
17
18	## Step 3 — Evaluate Against NSM Criteria
19
20	Score each candidate on the 5 NSM criteria (1–5 each):
21
22	1. Represents value: Does it go up when users genuinely get value, not just when they're active?
23
24	2. Predicts revenue: Is it a leading indicator of long-term revenue or retention? (Revenue itself is a lagging indicator — avoid as a primary NSM)
25
26	3. Measurable: Can you track it accurately with current infrastructure? Any data quality concerns?
27
28	4. Actionable: Can the product team run experiments that meaningfully move this metric?
29
30	5. Understandable: Can any team member immediately understand what this metric means? (Avoid complex composite metrics as NSM)
31
32	Score each candidate across all 5. The highest total score is the strongest candidate.
33
34	## Step 4 — The Vanity vs. Value Test
35
36	Apply the most important filter: does this metric go up even when users aren't getting value?
37
38	- Total signups: Goes up with any acquisition — users could sign up and never use the product
39	- Total sessions: Goes up if users open the app and immediately give up
40	- Total pageviews: Goes up with any traffic, regardless of engagement
41
42	Eliminate vanity metrics from consideration.
43
44	## Step 5 — North Star for Your Business Model
45
46	Cross-reference with the known best-practice NSM by business model (from memory context):
47
48	SaaS: "Weekly active users who complete [core action]" — captures genuine engagement, not just logins
49	Marketplace: "Completed transactions with positive outcome for both sides" — prevents optimizing for volume at the expense of quality
50	Consumer: "DAU/MAU ratio" — measures habit formation, not just reach
51	Usage-based: "Value-generating actions per period" — not all usage, specifically value-generating
52	Freemium: "Users who hit the activation threshold" — the specific action that predicts conversion
53
54	## Step 6 — Recommendation
55
56	Present:
57	- Ranked candidates with scores and rationale
58	- Recommendation with explanation
59	- Why the top alternative was rejected
60	- Any supporting metrics that should be tracked alongside the NSM
61	- One metric to explicitly exclude (and why — prevents gaming)
62
63	## Step 7 — Output
64
65	Produce:
66	- Evaluation table (all candidates × 5 criteria × scores)
67	- Final recommendation with rationale
68	- Supporting metric suite (3–4 metrics that indicate whether the NSM will move)
69	- Implementation note: if the recommended NSM isn't currently being tracked, what would it take to start?

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north-star-selection

70stars33forks

View on GitHub

How to install north-star-selection?

productfculty-aipm/pm-copilot-by-product-faculty/north-star-selection

$npx -y skills add Productfculty-aipm/PM-Copilot-by-Product-Faculty --skill north-star-selection

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# North Star Selection
2
3	You are helping the user choose the right North Star Metric from a set of candidates. This is different from defining a North Star from scratch — here, the user has options and needs a framework for deciding.
4
5	Framework: Lenny Rachitsky (North Star guide, survey of 40+ top companies), Sean Ellis (North Star selection criteria), Dan Olsen (prioritizing metrics).
6
7	## Step 1 — Load Context
8
9	Read `memory/user-profile.md` for product stage, business model, and current metrics. Read `context/company/analytics-baseline.md` for available metrics.
10
11	## Step 2 — Gather the Candidates
12
13	Ask: what metrics are being considered? For each candidate metric, capture:
14	- Name and definition
15	- How it's currently measured
16	- Who has access to this data
17
18	## Step 3 — Evaluate Against NSM Criteria
19
20	Score each candidate on the 5 NSM criteria (1–5 each):
21
22	1. Represents value: Does it go up when users genuinely get value, not just when they're active?
23
24	2. Predicts revenue: Is it a leading indicator of long-term revenue or retention? (Revenue itself is a lagging indicator — avoid as a primary NSM)
25
26	3. Measurable: Can you track it accurately with current infrastructure? Any data quality concerns?
27
28	4. Actionable: Can the product team run experiments that meaningfully move this metric?
29
30	5. Understandable: Can any team member immediately understand what this metric means? (Avoid complex composite metrics as NSM)
31
32	Score each candidate across all 5. The highest total score is the strongest candidate.
33
34	## Step 4 — The Vanity vs. Value Test
35
36	Apply the most important filter: does this metric go up even when users aren't getting value?
37
38	- Total signups: Goes up with any acquisition — users could sign up and never use the product
39	- Total sessions: Goes up if users open the app and immediately give up
40	- Total pageviews: Goes up with any traffic, regardless of engagement
41
42	Eliminate vanity metrics from consideration.
43
44	## Step 5 — North Star for Your Business Model
45
46	Cross-reference with the known best-practice NSM by business model (from memory context):
47
48	SaaS: "Weekly active users who complete [core action]" — captures genuine engagement, not just logins
49	Marketplace: "Completed transactions with positive outcome for both sides" — prevents optimizing for volume at the expense of quality
50	Consumer: "DAU/MAU ratio" — measures habit formation, not just reach
51	Usage-based: "Value-generating actions per period" — not all usage, specifically value-generating
52	Freemium: "Users who hit the activation threshold" — the specific action that predicts conversion
53
54	## Step 6 — Recommendation
55
56	Present:
57	- Ranked candidates with scores and rationale
58	- Recommendation with explanation
59	- Why the top alternative was rejected
60	- Any supporting metrics that should be tracked alongside the NSM
61	- One metric to explicitly exclude (and why — prevents gaming)
62
63	## Step 7 — Output
64
65	Produce:
66	- Evaluation table (all candidates × 5 criteria × scores)
67	- Final recommendation with rationale
68	- Supporting metric suite (3–4 metrics that indicate whether the NSM will move)
69	- Implementation note: if the recommended NSM isn't currently being tracked, what would it take to start?

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6 picks

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