Today, we’re launching agent-skills, our new public repository for reusable Statsig skills. It’s designed to help teams run common Statsig workflows faster and more consistently from AI agents.
Create Dashboard: Generate Statsig dashboards with a repeatable, structured workflow instead of manual one-off setup.
Create Cloud Metric: Define cloud metrics through a guided skill flow, including key configuration steps that are easy to miss in ad hoc API calls.
Skills turn complex Statsig workflows into repeatable, shareable agent instructions you can personalize or share and reuse across your team's projects. With Skills, you can direct your agents to execute multi-step logic, stitching together Console API calls, MCP tool calls, and prompt instructions.
Ensure you have a Console API Key -- this is required for the skill to carry out Statsig Console API actions.
Install the Statsig agent-skills repo with the Vercel skills CLI:
npx skills add statsig-io/agent-skills
Instruct your agent to use the skill (e.g., "Codex, help me create a cloud ratio metric for checkout rate).
Watch your agent follow your direction and the skill instructions to work with Statsig!
Explore the repo and start building repeatable Statsig workflows: statsig-io/agent-skills.
Statsig MCP now supports for both Segments and Layers, so you can more seamlessly manage user targeting and experiment configuration using your AI workflows.
View full segment definitions and create new segments (rule-based or ID-based)
Update existing segments, including rule-based segments and ID-based segment membership
View all layers and their parameter details
Create layers and create experiments with assignment to a layer
Segments and Layers are core building blocks for safe, precise experimentation. Segments unlocked faster targeting definition based on a set of users or rules. Layers unlocked cleaner parameter management under high experiment volume. Now, empowering your agents with these tools will help accelerate iteration velocity and improved engineering efficiency, all while maintaining safe and consistent experiment configurations.
If you have the Statsig MCP set up, try the below example prompts and workflows to explore the new segment and layers functionality:
"List all segments, then show details for the segment [segment_name].”
“Create a layer for shared signup experiment parameters.”
"Create an experiment testing new signup flow UI and add it to the signup_tests layer."
Learn more in the docs: Statsig MCP Overview.
Abort long-running queries from Metrics Explorer to reduce warehouse load and avoid unnecessary compute usage.
Prevent long-running queries from tying up warehouse resources
Avoid accidental full-dataset scans
Limit the cost impact of exploratory queries
Metrics Explorer queries can be canceled after 5 seconds when running on supported warehouse integrations (BigQuery, Databricks, Snowflake, and Athena). Query cancellation currently applies to individual charts and does not yet extend to dashboards.
Cancel Queries let you interrupt a run, refine the query, and try again immediately. This reduces unnecessary warehouse usage while keeping exploratory workflows fast and responsive.
Understand how users start, return, stay active, and churn over time. Lifecycle Charts classify user activity across time intervals to show how engagement evolves.
Understand product stickiness out of the box
Separate growth driven by new vs sustained engagement
Spot churn and reactivation patterns at a glance
Select an event, define a unique unit, and choose a time interval. Lifecycle Charts automatically classify activity by one of four lifecycle states:
New: Active in the current interval with no prior activity within the lookback window (up to one year)
Resurrected: Active in the current interval, not active in the previous interval, but had activity earlier in the lookback window
Recurring: Active in both the current and immediately previous interval, indicating continued engagement.
Dormant: Active in the previous interval but inactive in the current one, highlighting potential churn
Lifecycle Charts reveal why usage changes by showing shifts in engagement composition over time. Teams can distinguish growth from retention changes, identify drop-off earlier, and understand product stickiness without building custom retention analyses.
Check out our docs for more information.
You can now create dashboards via the Statsig Console API. This unlocks dashboard setup through code so teams can plug into internal tooling and automation, including Codex Skills.
Generate dashboards from an API request
Add time series, rich text, and categorical widgets
Integrate dashboard creation into workflows powered by tools like Codex Skills
Dashboards can now be managed at scale through code. Teams can automate setup to save time and integrate it with the tools they already use. The console remains available for exploration and refinement.
This feature is currently in private beta for Pro and Enterprise customers.
If you'd like access, reach out over Slack.
Add structure to dashboards by organizing widgets into focused sections. Dashboard Pages help teams separate workflows and context so related signals live together.
Navigate dashboards with clearer context
Group related widgets into dedicated views
Keep dashboards performant as they scale
Add pages inside a dashboard to organize widgets into distinct sections while keeping everything in one place.
Loading fewer widgets at once improves dashboard performance and responsiveness. Teams can move between workflows faster while working with large or complex dashboards
Stay informed on key metrics through scheduled dashboard reports. Dashboard Subscriptions deliver a PDF snapshot of your dashboard directly to Slack or email on a cadence you choose.
Receive automated dashboard snapshots in Slack or email
Schedule recurring updates for teams or stakeholders
Keep visibility on important metrics without manually checking dashboards
From any dashboard, open the “…” menu and select Add Dashboard Subscription. Configure the delivery schedule and subscribed audience. Statsig generates a PDF snapshot at the scheduled time and delivers a read-only version of the dashboard via Slack or email.
Dashboard Subscriptions makes it easier for teams to monitor ongoing trends asynchronously. Stakeholders receive recurring updates as dashboards update.
We’ve added a simple way to copy and share individual metric results—no formatting required.

With this update, you can:
Quickly copy individual metric data from experiment results
Share individual metric data as a snap shot or text
Whether you’re reporting results or discussing outcomes with your team, this makes it easier to communicate what matters. Feature is available today for all Statsig customers.
We rolling out an improved Switchback Experimentation model to WHN customers. The new Switchback experiment utilizes a regression-based analysis method that replaces our previous bootstrapping approach. This update brings greater flexibility and analytical power, including the ability to break down results by pre-computed dimensions, more configurable burn-in/out periods, and improved scheduling and clustering.
By alternating treatments over time for the same units, switchbacks help control for interference and capture more realistic system-level effects. Use a switchback experiment when you can’t reliably randomize at the user level—typically because treatments affect shared systems or environments (e.g., marketplaces, pricing, routing, or infrastructure).
Cutting over to the new Switchback model is a breaking change, and we’ll work closely with customers running legacy switchback experiments to plan a smooth migration. For customers who haven’t previously used switchback experiments in Statsig, the feature will be rolled out in the coming days. If you’re interested in learning more or getting started, feel free to reach out via Slack or your account manager.
Statsig Cloud customers can now run, interact, and display Power Analysis results directly in the setup page.

With Inline Power Analysis, you can:
Run and view power analysis results without switching to another page
Set and iterate on target MDEs and experiment duration
Instantly see recommended experiment duration based on your inputs
Quickly access results anytime—results are saved and visible on the setup page
This makes it easier to align on realistic expectations before you launch, ensuring your experiments are both efficient and statistically sound.
Inline Power Analysis is rolling out in the coming days to all of our Cloud customers.