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Trust your product data.

The signups, activations, and conversions you count on stop getting recorded, whether an agent rewrote the tracking, you changed it by hand, or never set it up. Skene stores your product metrics in your own Supabase, then runs autonomously after a one-time setup, so they're there the day you need them.

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The problem

You can't get today's data back tomorrow.

Early on, analytics is handled, for now. You will get to it properly later, the product comes first, and what you already have feels like enough. Then an event quietly stops firing, from a refactor, a rename, or because no one added it. Nothing errors. The table just stops filling.

Analytics is not retroactive. Months later you raise a round, set pricing, or chase a churn spike, you reach back for the history, and it is not there. You cannot backfill an event that never fired.

Kept in your own Supabase, every event costs cents to store and almost nothing to check on a PR. Being without it costs you the decision. Skene connects in under ten minutes and runs on every pull request, so the record is already there when it matters.

Event write indexing icon

Trust the data your decisions run on.

A baseline of every event write you already have.

  • Indexed by file, line, table, and payload
  • Reads your Supabase schema as the contract
  • Checks each PR against its preview branch, via Supabase branching
  • Read-only. Never writes or moves your data
  • Runs on every PR, before merge
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Starting journey analysis…

This may take a few minutes. Stay on this page to see live pipeline updates.

Analyzing Schema
Events from codebase
Generating Journey
Discovery
From sign up to account creation
SIGNALTYPEFOUND ATSTATUS
Account CreatedSupabasepublic.accountsCan be tracked (DB)
Signup Page ViewedGitHubapp/admin/(auth)/login/page.tsxRecommended
Signup Form SubmittedGitHubapp/admin/(auth)/login/page.tsxRecommended
Auth User CreatedSupabaseauth.usersCan be tracked (DB)
auth.users.insertGitHub–Can be tracked (DB)
user creates an account recordGitHub–Can be tracked (DB)
refactor: consolidate checkout flow tracking
Open
feat/checkout-v2→main
skenebotcommented now

Analytics diff detected

Missing callcheckout_started: not found in new state
Renamed eventpurchase_complete → order_confirmed
Payload shape changecart_viewed: field "items" removed
Conditional no longer firesupsell_shown: condition block unreachable
Caught on review. Not on a dashboard that's been wrong for weeks.
Broken event write detection icon

Never lose data you can't get back.

Every way an agent quietly breaks a write.

  • Removed or renamed writes
  • Wrong types, or payloads your schema cannot store
  • Conditional writes that stopped firing
  • Flagged as a PR comment, not weeks later
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Supabase schema alignment icon

Report numbers you can stand behind.

Tracking that compiles is not tracking that works.

  • Checks every event against its Supabase table
  • Catches renames that still pass your tests
  • Names the event, column, and what stops recording
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Analytics events
checkout_started
purchase_complete
cart_viewed
public·events
event_nametext
order_idint4
cart_itemsmissing
created_attimestamptz
Skene checking events against schema…
feat: add purchase_complete tracking
Open
feat/purchase-events→main
skenebotcommented now

Schema mismatch detected

purchase_complete→public.events
Type mismatchpayload.purchase_id · text → column is int4
Missing columnpayload.cart_items · column does not exist

From trustworthy tracking to revenue decisions.

A baseline of every event write you already have, with drift caught on the PR that introduced it. Then query that trusted data over MCP for the paths, cohorts, and features that drive revenue.

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1. EVERY EVENT WRITE, INDEXED AGAINST YOUR SCHEMA
2. DRIFT CAUGHT ON THE PR THAT INTRODUCED IT
3. THE PATHS AND COHORTS THAT PAY, OVER MCP

Four ways to plug Skene in.

MCP server for your coding agent. GitHub Action for CI. Cloud API for custom runs. One-time repo audit.

Start with a one-time repo audit, or wire the GitHub Action into CI. Same engine behind each.

Start freeRead more
MCP server
Cursor · Claude Code
GitHub Action
Runs on every PR
Cloud API
Any script, any time
Repo audit
One-time · no commitment
MCP server
Skene runs before the agent commits. Catches analytics issues in the agent loop, not after the PR lands.
skene mcp --cursor

Separation of duties

The agent writes the tracking. It should not grade its own work.

An agent checking the tracking it just wrote is the conflict of interest the check exists to remove. Skene runs alongside Cursor, Claude Code, and Codex, not inside them. The gate sits outside the tool that made the change.

It is not a dashboard you babysit or a copy of your data. Your data stays in your database. Skene owns the gate, and the trusted record you query over MCP for what drives revenue.

Built in the open,
with our design partners.

119 stars
Open GitHub
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See what your last 10 PRs quietly broke.

Start free, or install the open-source core. Your first repo audit runs in about as long as your CI does.

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Pay for cloud validation runs.

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  • Local MCP server
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