PostHog skills collection

Debugging Surveys

Diagnose PostHog Surveys configuration and responses across all five SDKs (web/posthog-js, iOS, Android, Flutter, React Native).

Designing Email Templates

Author, 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.

Diagnosing Ci And Merge Bottlenecks

Diagnoses 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 Performance

Diagnose 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.

Diagnosing Experiment Results

Diagnoses bias, anomalies, and strange results on a PostHog experiment. Covers 0-exposure experiments, sample ratio mismatch, identity fragmentation, multi-variant exposure, uneven-split exclusion bias, significance traps (peeking, A/A…

Diagnosing Failed Warehouse Syncs

Diagnose why a data warehouse sync is failing and recommend the right recovery action.

Diagnosing Missing Recordings

Diagnoses why a session recording is missing or was not captured.

Diagnosing SDK Health

Diagnoses the health of a project's PostHog SDK integrations — which SDKs are out of date and how to fix them.

Diagnosing Stacktrace Symbolication

Help users debug PostHog Error Tracking stack-trace symbolication for any supported platform — JavaScript/TypeScript web, React Native (Hermes), Android (Proguard / R8), or iOS / macOS (dSYM). The PostHog symbol-set lookup flow is…

Downloading Batch Export Files

Export PostHog events, persons, sessions, or the results of a HogQL query on demand and download the resulting files.

Exploring AI Failures

Find where an AI/LLM application is failing in production and surface the failure patterns, working from real traces.

Exploring Apm Traces

Investigates distributed application performance using PostHog APM (OpenTelemetry span) data via MCP.

Exploring Autocapture Events

Guides exploration of $autocapture events captured by posthog-js to understand user interactions, find CSS selectors (especially data-attr attributes), evaluate selector uniqueness, query matching clicks ad-hoc, and create actions.

Exploring Endpoint Execution Logs

Explore and diagnose a PostHog endpoint's execution logs — error messages, failed runs, cache misses, slow runs, or unexpected row counts during endpoint invocations.

Exploring Live Traffic

Inspects PostHog Web analytics Live tab data — current users online, last-30-minutes pageviews, top pages, referrers, devices, browsers, countries, bot traffic, and the per-minute bot/users charts.

Exploring LLM Clusters

Investigate AI observability clusters — understand usage patterns in AI/LLM traffic, compare cluster behavior, compute cost/latency metrics, and drill into individual traces within clusters.

Exploring LLM Costs

Investigate LLM spend in PostHog — total cost over time, cost by model, provider, user, trace, or custom dimension, token and cache-hit economics, and cost regressions.

Exploring LLM Evaluations

Investigate AI observability evaluations — hog (deterministic code-based), llmjudge (LLM-prompt-based), and sentiment (user-message sentiment). Find existing evaluations, inspect their configuration, run them against specific generations…

Exploring LLM Traces

Debug and inspect LLM/AI agent traces using PostHog's MCP tools.

Exploring MCP Intent Clusters

Explore PostHog MCP intent clusters — agent goals grouped by semantic similarity, with each cluster's tool distribution and error rates, plus the tool-centric pivot (capture rate per intent, discovery rate against the advertised catalog…