---
title: "Product demo: from signup to pull request | Skene"
description: "See Skene in six steps, from email signup to a pull-request review. Every screen shows real product output, the missing events included."
url: https://www.skene.ai/demo
doc_version: "76871e0a800e"
last_updated: 2026-10-30
---

Product demo

# A product demo from signup to pull request.

This product demo follows a GTM team’s growth question through Skene’s own workspace to the fix you review. Every screen shows real product output, including the five events Skene found missing in its own code.

[Start free](https://www.skene.ai/signup) [Read the quickstart](https://www.skene.ai/resources/docs/cloud/quickstart)

## Follow one question through the product.

Captured from the live app on 29 October 2026. Redrawn screens keep the app’s text.

One question, six steps Select a step to inspect

### Start with your email. One source is enough.

A magic link signs you in, with no password or card. Connect GitHub or Supabase and the first analysis is free. A Supabase auth schema alone gives 11 events.

**Events**

0 code events 11 database events

Database

| Event | Source | Found at | Status |
| --- | --- | --- | --- |
| email_change_requested | Supabase | auth.users | Can be tracked (DB) |
| email_changed | Supabase | auth.users | Can be tracked (DB) |
| email_confirmed | Supabase | auth.users | Can be tracked (DB) |

The first 3 of 11 rows on the Events page, Demo workspace. Redrawn.

### Ask the question in plain words.

The Agent page takes the question your GTM team brings you, not a query. Six teams each get a set of questions to start from.

- Can we tell whether acquisition events are tied to a known user or anonymous visitor?

- Can connected analytics sources support attribution by provider and source role?

- Do ingested analytics events carry the properties needed to identify an acquisition path?

Marketing ops questions on the Agent page in skene-web. Redrawn.

### Skene names what’s missing.

Asked how to raise retention, Skene took 14 investigation steps and named the five events the answer needs, with reasons. All five were missing from Skene’s own code.

Agent **I want to increase retention with our customers**

14 investigation steps

To answer this question we need the following events:

| Event | Why | Parameters | Status |
| --- | --- | --- | --- |
| `first_value` | This marks when an account reaches the product outcome, which is the key point to measure retention from. | `plan` `timestamp` | Not found |
| `feature_used` | This shows which parts of the product customers keep returning to after activation. | `feature` `plan` `timestamp` | Not found |
| `onboarding_step_completed` | This identifies where customers stop during setup, which helps find early drop-off that hurts retention. | `step` `timestamp` | Not found |
| `subscription_cancelled` | This captures churn directly so you can measure how retention changes over time. | `plan` `timestamp` | Not found |
| `support_ticket_opened` | This helps connect support issues to later churn or repeated use patterns. | `timestamp` | Not found |

Open coverage

A saved Agent answer in skene-web. Redrawn.

### Hand the fix to your coding agent.

How to fix turns the gap into a brief for a coding agent: where each call goes and what it sends.

How to fix

Recommended fix

Add analytics calls for the smallest set of events required to answer the retention question, and include every required property exactly as listed:

1. `first_value`
  Add in the setup or onboarding flow where an account reaches the product outcome.
  Send plan and timestamp.

2. `feature_used`
  Add at the point of feature interaction.
  Send feature, plan, and timestamp.

The first two of five How to fix items. Redrawn.

### Ask Skene from your editor.

Cursor connects with a workspace API key and one configuration block. Your agent then gets 11 Skene tools, including a tracking review before you push.

**Skene MCP**

1. Add the connection to your client Cursor Manual setup
  Copy configuration
  Merge into your Cursor MCP configuration.
  { "mcpServers": { "skene": { "url": "https://www.skene.ai/api/mcp", "headers": { "X-API-Key": "YOUR_WORKSPACE_API_KEY" } } } }
  Replace `YOUR_WORKSPACE_API_KEY` with your key before saving.

The connection step on the Skene MCP page. Redrawn.

`skene_analytics_review` over MCP on a working-tree diff. Screenshot, cropped.

### Catch the break on the pull request.

With PR reviews on, the Skene GitHub App checks every diff. Here it flags `watch_demo` renamed to `demo_watch` and suggests restoring the old name.

A Skene GitHub App review on a pull request. Screenshot.

## Start with the free audit.

[Start free](https://www.skene.ai/signup)

Create a workspace and connect a source. One free audit per workspace, no card required.

## Sitemap

- [Markdown sitemap](https://www.skene.ai/sitemap.md): every page on this site, with its markdown counterpart.
- [Index for language models](https://www.skene.ai/llms.txt): the same set as a link-dense index.
- [Full corpus](https://www.skene.ai/llms-full.txt): reference content concatenated as plain text.