launch-review
Skill0 starsChanged 28 days agoMITView on GitHub
Analyze a product launch's funnel from the user's numbers — visitors by channel, signups, purchases, refunds — find the single biggest bottleneck, and propose the next three experiments. Use 7 days after a launch, or when the user asks "how did the launch go" or "why aren't people buying".
4 other projects use a version of this.
Adopted by
Most recently taken up by
- kritikosgns-web/indie-launch-skills-liteword for word, first seen Oct 20, 2026
- 2104178150-ai/megaphonetheir own version, first seen Oct 20, 2026
- timscheuerai/launch-video-kittheir own version, first seen Sep 27, 2026
- anthropics/claude-for-legaltheir own version, first seen May 15, 2026
Other versions4 projects use a version of this.
Word for word · 1
- kritikosgns-web/indie-launch-skills-lite★ 0100% same
Edited · 0
None found.
Wrote their own version · 3
- anthropics/claude-for-legal★ 9.5ksame name
- timscheuerai/launch-video-kit★ 16same name
- 2104178150-ai/megaphone★ 5same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repositoryOne other file it gives its agents.
- positioningSkill
The file
We split this skill into the rules it gives an agent
2 rules. 0 are common, 2 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 30
Never call a result from fewer than 20 conversions or 100 visitors without labeling it "too early".
- Distinctive: line 32
If refunds > 10% of purchases, refunds become the bottleneck regardless of the funnel.
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Launch Review
Numbers decide what to fix. One bottleneck, three experiments, nothing else.
Inputs (accept messy pastes)
- Visitors by channel (UTM source) for the period
- Signups / trials, purchases, revenue, refunds
- Pricing-page and checkout visits if tracked
- What the user changed during the period
Analysis
- Funnel table: visits → signup/trial → purchase, with conversion % per step and per channel.
- Compare to rough benchmarks, labeled as rough: landing → signup 2–5% for cold traffic, 10–25% for warm (own list); trial → paid 10–25%; checkout start → purchase 40–70%.
- Bottleneck = the step furthest below its benchmark that has enough volume (≥ 100 visitors or ≥ 20 events). With less volume, the bottleneck is traffic itself; say so.
- Channel ranking by purchases per 100 visitors, not by raw traffic.
Experiments
Three experiments, all aimed at the bottleneck, each with: change · metric · minimum sample before judging · expected direction. Rank by effort (smallest first).
Rules
- Never call a result from fewer than 20 conversions or 100 visitors without labeling it "too early".
- Separate one-off launch spikes from steady daily traffic.
- If refunds > 10% of purchases, refunds become the bottleneck regardless of the funnel.
Output
Funnel table, bottleneck (one sentence), channel ranking, three experiments, and the date to rerun this review.
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.

