A wrongly set-up experiment still produces numbers, and they are the wrong numbers. This goes through every experiment and feature flag in a project, grades what it finds worst-first, and puts a fix beside each one.
WHEN TO USE
SCOPE
USE FOR
Check whether a single feature flag or experiment is configured correctly before trusting it.
Run a full health check across every experiment and flag in a project at once.
Find feature flags that are stuck, unstable, or never got activated.
Catch an experiment whose linked feature flag is paused so traffic silently isn't splitting.
This is a saved copy of the skill's SKILL.md instructions. It may differ from the upstream file or the version you install.
Auditing experiments and feature flags
This skill teaches you how to run configuration audits on experiments and feature flags.
All checks use the experiment and feature flag read tools (experiment-get, experiment-list, feature-flag-get-definition, feature-flag-get-all) — no SQL queries are needed for Phase 1 checks.
Usage modes
Quick check (single entity)
When the user asks about a specific experiment or flag:
Fetch the entity via experiment-get (experiment ID) or feature-flag-get-definition (numeric flag ID).
If there are more than 5 entities with findings, write them to a notebook for easier navigation. Otherwise report inline. Create the notebook from the project's own notebook tools. Run search notebooks?- to load them and read the titles.
🟡 WARNING — Flag integration · Experiment: checkout-redesign
The linked feature flag is inactive (paused). Traffic is not being split.
Action: Re-enable the flag or end the experiment.
Handling unavailable data
Some checks require activity logs (feature-flags-activity-retrieve for flags), which may not be available in every session.
If activity log data is unavailable:
Connect PostHog's MCP server with experiment and feature-flag read tools (experiment-get, experiment-list, feature-flag-get-definition, feature-flag-get-all) so the audit can fetch your project's experiments and flags.
Listed as free
Connected services may require an account or charge fees.
Installation
One command — usually under 2 minutes.
🔌 This skill ships inside the PostHog AI Plugin. Listed package contents include 3 slash commands, 1 agent, hooks and an MCP server. Installed components and skill versions may vary by AI tool.
Install just this skill
Run this outside your AI tool, using Node.js 22.20.0 or newer. Skills CLI 1.7.2 skips skill selection; prompts cancel installation without an interactive terminal. If choosing Project when asked about installation scope, open your project's folder before running this.
Install checklist
Check selected tools if a picker appears; Claude Code may be unchecked under Additional agents. ↑/↓ moves, Space toggles selections, Enter confirms.
Without a tool picker, check Installing to: for your intended tool. Stop if it names a different tool.
If asked, choose Symlink (Recommended) for shared files or Copy to all agents for separate copies; review the summary before confirming installation.
Install the find-skills skill? defaults to Yes, adding another skill for all projects. Choose No if you don't want that extra installation.
Skills CLI 1.7.2 sends install data to skills.sh by default, including the source, skill names, target tools and file details; GitHub sources are reported only when GitHub confirms the repository is public, while other remote sources can also be reported. Confirmed-public GitHub sources also trigger a security-audit request. Before installing, set the environment variable DO_NOT_TRACK=1 or DISABLE_TELEMETRY=1 to disable both.
After installing for Claude Code, open it in the installation project if you chose Project; Global makes the skill available across projects on this computer. Once Claude Code loads the skill, its description helps Claude decide when to use it.
If installation created a top-level skills folder that did not exist when your Claude Code session started, run /reload-skills in that session. Run it again after later changes in that folder.
MCP server required
The skill's steps call for tools from the PostHog MCP server. Installing just this skill doesn't add that connection; set it up in your AI tool if it isn't there yet: PostHog MCP setup. Installing the whole plugin instead includes the connection settings.
Requirements for the PostHog MCP server
Connecting is free; sign in with your PostHog account.
Some tools use AI internally and may incur PostHog AI charges. Those tools require AI data processing to be enabled in your organization settings.
Install the whole plugin
This route installs the posthog plugin package selected for your AI tool.
Claude Code
Add PostHog's marketplace, then install the plugin
Run both lines in a terminal. They install PostHog's posthog plugin: this skill, PostHog's other skills, and a connection to PostHog's hosted MCP server.
01
claude plugin marketplace add PostHog/ai-plugin
02
claude plugin install posthog@posthog
Installation and loading
The plugin installs for you in every project and loads the next time you start Claude Code, or after /reload-plugins in an open session.
To connect your PostHog account, start claude, type /mcp, select plugin:posthog:posthog and follow the browser prompts.
Good to know
The plugin includes PostHog's session-capture hook; PostHog's README says it sends sessions to LLM Analytics only when POSTHOG_LLMA_CC_ENABLED=true and POSTHOG_API_KEY are both set.
If you use the separate posthog-telemetry plugin, PostHog says to keep only one of the two, because both register the same hook.
On a self-hosted PostHog, this route's MCP connection won't reach your instance: the plugin's config is fixed to https://mcp.posthog.com/mcp, which routes to PostHog's US or EU region. POSTHOG_MCP_URL works only for the Gemini CLI extension.
Sync columns from a synced data warehouse table onto PostHog person or group properties, so warehouse data becomes usable anywhere person and group properties already work: feature flag targeting, cohorts, insight filters and breakdowns, surveys, session replay filters, workflows, and the person profile. Use when the user wants to "add a person property from my warehouse", "enrich people with Stripe/Postgres/Salesforce data", "put ARR or plan tier on my persons", "target a feature flag by a warehouse column", "sync warehouse columns onto groups or organizations", or wants to inspect, backfill, disable, or debug an existing warehouse-backed person or group property.Read full description
Analyze the most expensive users in AI observability and explain why they cost so much. Use when the user asks about top spenders, expensive users, per-user LLM cost, user-level cost drivers, or patterns behind high AI observability spend.Read full description
Analyze session replay patterns across experiment variants to understand user behavior differences. Use when the user wants to see how users interact with different experiment variants, identify usability issues, compare behavior patterns between control and test groups, or get qualitative insights to complement quantitative experiment results. Also covers pairing the observed behavior with a linked survey when the user wants qualitative feedback beyond what recordings show.Read full description
Assesses what a page's heatmap is telling you and recommends concrete changes. Pulls click / rageclick / scroll-depth data for a URL, names the hot elements by cross-referencing autocapture events on the same page, and can create a saved heatmap the user opens in PostHog, then summarizes the behavior and proposes improvements.
TRIGGER when: user asks what a heatmap shows, why people aren't clicking something, where users rage-click, how far they scroll, what to change on a page based on heatmap/click data, or to 'analyze/assess/review the heatmap' for a URL.
DO NOT TRIGGER when: the user only wants to create a saved heatmap screenshot with no analysis (use heatmaps-saved-create directly), or is asking about session replay in general (use investigating-replay).Read full description
Audit every endpoint in a PostHog project for staleness, failed materialisations, and unused materialised versions. Use when the user asks "what endpoints can I clean up?", "are any of my endpoints broken?", "which materialised versions are still being called?", or wants a one-shot cleanup pass over the Endpoints product. Produces a prioritised report grouped by issue type, with recommended actions but does not modify anything without explicit confirmation.Read full description
Audit the health of a PostHog project's data warehouse sources and syncs — find every broken or degraded source connection, sync schema, and webhook channel. Use when the user asks "why are my imports failing?", "what's broken with my sources?", "why is my warehouse data stale?", or wants a one-shot triage of source/sync health before deciding where to dig in. Produces a prioritized report grouped by severity, with recommended next steps. For materialized-view health use auditing-warehouse-view-health; for a single failing sync use diagnosing-failed-warehouse-syncs.Read full description
