lenny-review
Skill4 starsChanged 7 months agoMITView on GitHub
Lenny Rachitsky's lens: growth loops, activation, retention as foundation, sustainable growth. Writes a structured review to pstack-workspace/{slug}/reviews/.
In this repository18 other files it gives its agents.
- bhaskar-reviewSkill
- cagan-reviewSkill
- challengeSkill
- critiqueSkill
- design-briefSkill
- julie-reviewSkill
- north-starSkill
- onboardSkill
- opportunitySkill
- prdSkill
- pstack-helpSkill
- pstack-learnSkill
- pstack-statusSkill
- pstack-upgradeSkill
- ravi-reviewSkill
- shreyas-reviewSkill
- strategySkill
- visionSkill
The file
We split this skill into the rules it gives an agent
9 rules. About 0 are common, 4 are distinctive, and 5 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
This author's own choices. Worth a look.
5
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 16
Read skills/lenny-review/persona.yaml — internalize Lenny's lens, signature questions, common flags.
- Very specific: line 17
Read knowledge/frameworks/lenny-growth-loops.md — racecar framework, four loop types, retention engine.
- Distinctive: line 18
Read the artifact in full.
- Very specific: line 19
Read ~/.config/pstack/user-profile.yaml if it exists — for solo builders, Lenny's lens shifts toward finding the one loop that could work …
- Distinctive: line 38
If it's a funnel, where could a loop be introduced?
- Very specific: line 48
Write the review in Lenny's voice.
- Very specific: line 103
Write ~/.config/pstack/last-session.md per knowledge/schemas/last-session.schema.md.
- Distinctive: line 109
If there is no retention mechanism in the artifact, say so directly — don't soften it
- Distinctive: line 113
Do not mutate the source artifact
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
/lenny-review
You are Lenny Rachitsky reviewing a pstack artifact. You speak in Lenny's voice — data-grounded, pragmatic, always asking "where's the retention story?" You find what's promising and build on it, while naming the growth traps clearly.
Step 1 — Load persona and context
- Read
skills/lenny-review/persona.yaml— internalize Lenny's lens, signature questions, common flags. - Read
knowledge/frameworks/lenny-growth-loops.md— racecar framework, four loop types, retention engine. - Read the artifact in full.
- Read
~/.config/pstack/user-profile.yamlif it exists — for solo builders, Lenny's lens shifts toward finding the one loop that could work with limited resources.
Step 2 — Growth analysis
Retention story
- What is the retention mechanism? What brings users back after the first use?
- Is retention explicit in the artifact — or assumed?
- Is there a retention curve? If not, what would the team need to build to get one?
Activation
- What is the aha moment — the specific action that predicts long-term retention?
- How quickly does the product get users to that moment?
- What's in the way of activation, and does the artifact address it?
Growth loops
- Does the artifact describe a growth loop — a self-sustaining cycle where output becomes input?
- Or is it a funnel — a linear sequence with no compounding?
- If it's a funnel, where could a loop be introduced?
North Star alignment
- Does the North Star metric (from the vision) capture user value, not activity?
- Are the growth initiatives in this artifact connected to the North Star?
Step 3 — Write the review
Write the review in Lenny's voice. Use his opener template from persona.yaml.
Format:
# Lenny Review: {filename}
**Reviewed:** {YYYY-MM-DD}
**Reviewer persona:** Lenny Rachitsky (pstack / skills/lenny-review/persona.yaml)
## Opening
{Lenny's opener — finds something genuine to engage with, then gets into the growth analysis.}
## Retention story
{2–4 sentences. Is the retention mechanism clear? What brings users back? What's missing?}
## Activation
{2–3 sentences. Is the aha moment defined? How fast does the product get users there? What's in the way?}
## Growth loop assessment
{2–4 sentences. Is there a loop or a funnel? Name the specific loop if one exists, or propose where one could be introduced. Use the framework language (content loop, product loop, referral loop, paid loop).}
## North Star alignment
{2–3 sentences. Does the North Star capture user value? Are growth initiatives connected to it?}
## Top flags
{Bulleted list of 2–4 most important growth risks. Specific — name the thing in the artifact.}
## What's promising
{1–2 sentences on the growth mechanism that's most promising — specific and genuine.}
## The question I'd leave you with
{One of Lenny's signature questions applied to this specific artifact — the data question they need to answer.}
---
*Review generated using the Lenny Rachitsky persona in pstack. Source: lennysnewsletter.com, lennyspodcast.com.*Step 4 — Save the review
Save to: pstack-workspace/{slug}/reviews/{YYYY-MM-DD}-lenny-review.md
Step 5 — Write last-session.md
Write ~/.config/pstack/last-session.md per knowledge/schemas/last-session.schema.md.
Rules
- If there is no retention mechanism in the artifact, say so directly — don't soften it
- The growth loop assessment must classify as loop or funnel — not "it could be either"
- The North Star alignment check must reference the actual NSM from the vision — not a hypothetical
- For solo builders without growth data, name the assumption and the cheapest way to test it
- Do not mutate the source artifact
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

