Official PostHog plugin for Claude Code, Cursor, Gemini, Codex and other AI coding tools
安装
npx skills add PostHog/ai-plugingh skill install PostHog/ai-plugingit clone --depth 1 https://github.com/PostHog/ai-plugin合集内的技能
- Adding Warehouse Person PropertiesPostHogSync 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.
- Analyzing Expensive UsersPostHogAnalyze 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.
- Analyzing Experiment Session ReplaysPostHogAnalyze 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.
- Analyzing Funnel CorrelationPostHogFind the events and person properties that correlate with funnel conversion or drop-off. Use when the user asks why people convert or drop off in a funnel, what converters do differently, which events or properties predict success or failure, or asks for "correlation analysis" on a funnel. Computes odds ratios with HogQL, because PostHog has no built-in funnel correlation view.
- Analyzing Offline EvaluationsPostHogInspect and compare offline AI evaluation experiments, diagnose case-level regressions, and follow scorer history across application, model, or prompt changes. Use when a user asks whether an offline run improved, why a case failed, how scores changed between runs, or how to publish externally computed offline results.
- Analyzing Task RunsPostHogSplit a completed PostHog task run into activity records — what the agent tried, whether it worked, what blocked it — and record each one through the report_activity tool. Use when a task asks to analyze a run, produce a task analysis, or review a run from an attached run log.
- Auditing EndpointsPostHogAudit 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.
- Auditing Experiments FlagsPostHogAudit PostHog experiments and feature flags for configuration issues, staleness, and best-practice violations. Read when the user asks to audit, health-check, or review experiments or feature flags, check flag hygiene, or verify experiment setup.
- Auditing Warehouse Source HealthPostHogAudit 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.
- Auditing Warehouse View HealthPostHogAudit the health of a PostHog project's materialized views (saved queries) — find every failed materialization and flag unused or stale materialized views that cost storage and compute. Use when the user asks "which of my views are broken?", "why is this materialized view failing?", "are any of my views wasting compute?", or wants a one-shot triage of view health.
- Authoring Data Quality ChecksPostHogAdds and runs data quality checks (dbt-test style assertions) on a project's warehouse tables and saved-query views, and HogQL catalog metrics: not-null, uniqueness, accepted values, referential integrity, row-count bounds, freshness, and custom HogQL. Metrics support custom SQL checks only.
- Authoring Error Tracking AlertsPostHogAuthor error tracking alerts that fire when an issue is created, reopened, or starts spiking. Use when the user asks to set up error notifications, route exceptions to Slack/webhook/Linear, or evaluate which error events are worth alerting on. Covers trigger-event selection, integration choice, dedup against existing alerts, and shipping with the canonical message body shape.
- Authoring Log AlertsPostHogAuthor useful, low-noise log alerts on services in a PostHog project. Use when the user asks to set up alerts for their logs, suggest alerts they should add, or evaluate whether a service is worth monitoring. Covers service triage, baseline characterisation, threshold drafting, back-testing via simulate, and shipping with a notification destination.
- Authoring ScoutsPostHogWrite, edit, and adapt PostHog Signals scouts: scheduled agents that scan a project and report findings. Use to change a canonical scout's scope, thresholds, schedule, or dry-run settings; add a scout for an uncovered surface; record structured output from scheduled LLM scoring; or give feedback through notes.
- Building A DashboardPostHogBuild a new dashboard, or update an existing one, from a set of insights — the same job the in-app assistant does with its upsert-dashboard tool, but over MCP. Use when a user asks to create a dashboard, put several metrics/charts together on one page, assemble a dashboard for a topic (product analytics, retention, revenue, activation, etc.), or add/remove/replace insights on a dashboard they…
- Building CanvasesPostHogCreate or edit a PostHog freeform canvas — a sandboxed browser application (data board, document, form, small tool, graphics experiment) stored in PostHog and rendered by the desktop/web app. Use when a task asks to build, generate, update, or fix a standalone canvas app, or when a freeform canvas id is given as the publish target.
- Building Html CanvasesPostHogAuthor a PostHog canvas with semantic HTML, CSS, and direct browser APIs — documents, articles, generative graphics, 2D canvas and WebGL experiences, and focused experiments where React components add no useful structure. Use after building-canvases has routed a canvas request to a plain-HTML/browser-API implementation.
- Building LoopsPostHogBuild a Loop for PostHog Desktop: a workflow that creates an AI task each time its trigger fires, optionally followed by a Slack or email notification with the task's result. Use when asked to create, set up, or change a loop, a recurring agent, a scheduled task, or an automation that runs an AI task when a GitHub, Slack, or PostHog event happens.
- Building React Quill CanvasesPostHogAuthor the React + Quill implementation of a PostHog canvas: the single-component contract, the allowed imports, Quill (PostHog's design system) component and composition rules, theme-aware design tokens, loading skeletons, and the in-canvas date picker.
- Building WorkflowsPostHogBuild, edit, test, enable, and monitor PostHog workflows over MCP. Author the action/edge graph so it runs and opens cleanly in the visual editor, then change drafts surgically with patch operations. Use when asked to build, set up, automate, change, fix, or debug a workflow, campaign, broadcast, drip sequence, or event-triggered automation in the workflows product, including first-time…
- Checking Deploy TimingPostHogDetermine when a PostHog code change reached a given environment by reading the hidden GIT deploy annotations in the project and correlating them with the merge commit on GitHub. Use when PostHog staff ask "when was X deployed", "is my change live in the US/EU yet", "has my PR shipped", "did the fix roll out to prod-us", or otherwise want to know whether/when a commit, PR, or feature went out to…
- Checking Member AccessPostHogExplains what a member or a role can do in a PostHog project, using the access control MCP tools. Use when the user asks what someone can see or edit, who can edit dashboards or feature flags, why a member can or cannot open a dashboard, notebook or table, what a role grants, which properties are hidden from someone, or how the project's default access is set.
- Choosing Trend Or Slope ViewPostHogClarify how to visualize change over a time range before building a trend. Use whenever the user asks how much something changed, grew, dropped, improved, or regressed between two points or periods — "how much did X change from A to B", "before vs after", "start vs end", "week over week", "compare this month to last", "change over time" — or mentions a "slope chart" / "slopegraph".
- Cleaning Up Stale Feature FlagsPostHogIdentify stale feature flags in a PostHog project and clean up the code that checks them. Use when the user wants to find, audit, or remove unused, fully rolled out, or abandoned feature flags, run a feature flag hygiene review or a weekly cleanup, reduce feature flag tech debt, or asks "which flags can I remove?".
- Composing Grid CanvasesPostHogCompose PostHog grid canvases — widget grids (including the user's home canvas) built from reusable component canvases. Use when a task asks to add, fill, move, resize, or remove a widget on a grid or home canvas, to compose a whole canvas of widgets from one ask, to build a reusable widget/component, or when a placement id or grid canvas id is the target.
- Configuring Experiment AnalyticsPostHogConfigures the analytics side of a PostHog experiment — exposure criteria (server-resolved default exposure event vs custom exposure events), primary and secondary metrics, the supported metric types (count, sum, ratio with `math` and `math_property`, retention with `retention_window_start` and `start_handling`), multivariate user handling ("Exclude from analysis" vs "Use first seen variant")…
- Configuring Experiment RolloutPostHogConfigures the rollout shape of a PostHog experiment — the variant split (50/50, 80/20, A/B/C ratios), the overall rollout percentage that gates how many users enter the experiment, and the disambiguation when a percentage like "roll out to 25%" could mean either.
- Consuming Endpoints From Client CodePostHogWire a PostHog endpoint into a client app or SDK. Covers fetching the OpenAPI spec, generating a typed client with openapi-generator or @hey-api/openapi-ts, sending the right auth header, shaping the variables payload (HogQL code_name vs insight breakdown property), handling rate-limit and materialised-endpoint error responses.
- Context Layer ConsolidationPostHogKeep the context wiki coherent using the deterministic lint report queue
- Context Layer DreamingPostHogSynthesizes recent organizational activity into a durable context wiki. Use when running a nightly or incremental context-layer dream, or when updating sourced organizational context from completed work.
- Context Layer Health CheckPostHogReviews context wiki quality after deterministic consolidation. Use when recent wiki-miss entries, contradictory or unsupported claims, stale priorities, near-duplicate subjects, or concepts without an owning page need semantic triage.
- Copying Endpoints Across ProjectsPostHogCopy a PostHog endpoint (a saved HogQL/insight query exposed as an API route) to another project in the same organization, or duplicate it under a new name in the same project. Use when the user wants to duplicate an endpoint, promote an endpoint from staging to production, replicate an endpoint's query/variables/freshness config in another workspace, or clone an endpoint to iterate on it.
- Copying Flags Across ProjectsPostHogCopy a feature flag from one PostHog project to one or more target projects in the same organization. Use when the user wants to duplicate a flag, promote a flag from staging to production, sync flags across projects, or replicate a flag configuration in a different workspace.
- Creating Ai SubscriptionPostHogCreate a recurring AI-generated PostHog report — schedule a free-text prompt to run on a cron, with the LLM-synthesized markdown delivered to email, Slack, or Microsoft Teams on each tick. Use when the user wants a recurring AI summary of X on any cadence (daily, weekly, monthly, yearly) rather than a one-off report.
- Creating An EndpointPostHogCreate a PostHog endpoint with the right shape on the first try — covers query kind choice, name conventions, what to expose as variables (HogQL code_name vs insight breakdown), data_freshness_seconds, and whether to materialise on day one. Use when the user says "create an endpoint", "expose this query as an API", "turn this insight into an endpoint", or asks for help structuring a new endpoint.
- Creating Box Plot InsightsPostHogCreates product analytics or SQL-backed box plot insights in PostHog. Use when a user asks to create, build, or save a box plot, visualize a numeric distribution, compare quartiles or medians across dates or groups, or turn SQL results into a box plot. Chooses between a standard Trends box plot and a SQL insight, validates the distribution data, saves the insight, and verifies it.
- Creating ExperimentsPostHogGuides agents through experiment creation: reading the project's setup with experiment-setup-context, defining the hypothesis, configuring rollout and bucketing, setting up analytics and running time, and reporting which choices are guesses. Delegates rollout decisions to configuring-experiment-rollout and metric setup to configuring-experiment-analytics.
- Creating Online EvaluationsPostHogAuthor continuously-running online evaluations in PostHog AI observability, grounded in real failure modes you've identified. Use when the user wants evaluations that automatically score new generations or whole traces going forward — "create an eval to catch X", "continuously check that responses do Y", "turn these failures into evals".
- Creating Replay Vision ScannersPostHogGuides agents through creating and safely sizing a Replay Vision scanner: choosing the scanner type (monitor/classifier/scorer/summarizer), shaping the RecordingsQuery that selects sessions, and — crucially — estimating the credits it will spend and checking the org's remaining budget before creating, so a broad scanner doesn't exhaust the budget on its first scheduled sweep.
- Creating SurveysPostHogCreates and launches PostHog surveys through MCP, including NPS/CSAT popovers, hosted feedback forms, and headless surveys. Guides survey type selection, audience targeting, draft review, and launch readiness. Use when asked to create a survey or form, or before calling survey-create. For investigating an existing survey's delivery or responses, use debugging-surveys instead.
- Debugging ExperimentsPostHogDebug and support PostHog Experiments (A/B tests) for a customer looking at their own results. Use whenever an experiment support ticket is pasted or a customer asks a results question, most commonly "why aren't my exposures even?", "why is one variant getting no traffic?", "why am I missing / seeing too few exposures?", "why does the bias banner show?", or "why don't PostHog's numbers match my…
- Debugging Failed Data Quality ChecksPostHogFinds out why a data quality check failed or errored, looks at the rows it matched, and recommends the fix. Also covers a materialized view refresh that the data quality gate did not publish. Use when asked why a check is red, what rows failed, why a view shows "Not published", why a view's data is stale after a refresh, or how to get a blocked refresh published.
- Debugging SurveysPostHogDiagnose PostHog Surveys configuration and responses across all five SDKs (web/posthog-js, iOS, Android, Flutter, React Native). Use whenever a Surveys support ticket is pasted ("survey not showing", "fewer responses than expected", "responses disappeared", "responses are incomplete", "only the first question was answered", "the user says they didn't mean to submit", "survey shows on wrong…
- Designing Email TemplatesPostHogAuthor, save, and edit email templates in the PostHog workflows library — compose email design JSON with Liquid personalization and create and round-trip-edit templates over MCP. Use when asked to design, build, update, or fix an email template for workflows, broadcasts, or campaigns.
- Designing Replay Vision ScannersPostHogDesigns a Replay Vision scanner that produces trustworthy observations: one visible question per scanner, a type chosen from the answer shape, a query that selects only sessions able to answer it, a prompt that demands on-screen proof and allows no or inconclusive, a model picked by the cost of a wrong answer, and a first-batch test pass.
- Diagnosing CI And Merge BottlenecksPostHogDiagnoses CI and pull-request pipeline health for a GitHub repo using the engineering analytics MCP tools — pull-requests (PR list with CI status), workflow-health (per-workflow CI trends), and pr-lifecycle (a single PR's timeline).
- Diagnosing Endpoint PerformancePostHogDiagnose why a PostHog endpoint is slow or expensive and propose a concrete fix — bump the cache TTL, enable materialisation, restructure variables, or rewrite the query. Use when the user says "this endpoint is slow", "my endpoint times out", "we're hitting the cost cap on this one", or asks "should I materialise this?". Focuses on a single named endpoint, not a project-wide audit.
- Diagnosing Experiment HealthPostHogRuns diagnostics and a health check on one PostHog experiment: its setup, exposures, results and changes during the run. Covers 0 exposures, sample ratio mismatch, lost or uneven exposures, users in multiple variants, identity faults, who the experiment counts, significance traps (peeking, A/A, 'target reached', Bayesian vs Frequentist, sequential, CUPED), mid-run edits, pause and freeze, and…