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signals
Cursor Skill
How to query the document_embeddings table for raw signal data using HogQL. Use when you need to perform semantic search over signals, fetch every signal that contributed to a specific report, or list signal types. For browsing the curated report layer (the Inbox) — listing reports, filtering by status/source, drilling into a single report by ID — use the `inbox-exploration` skill first; drop into this skill afterwards if the user wants the underlying observations.
Access PostHog analytics, feature flags, experiments, error tracking, and insights directly from Cursor
Skills39
analyzing-experiment-session-replaysAnalyze 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.
auditing-experiments-flagsAudit 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-data-healthAudit the health of a PostHog project's data warehouse — find every broken or degraded pipeline item across sources, sync schemas, materialized views, batch exports, and transformations. Use when the user asks "what's broken in my warehouse?", "give me a health check", "audit my data pipeline", "why are some dashboards stale?", or wants a one-shot triage summary before deciding where to spend time. Produces a prioritized report of issues grouped by severity and type, with recommended next steps.
cleaning-up-stale-feature-flagsIdentify and clean up stale feature flags in a PostHog project. Use when the user wants to find unused, fully rolled out, or abandoned feature flags, review them for safety, and then disable or delete them. Covers staleness detection, dependency checking, and safe removal workflows.
configuring-experiment-analyticsConfigures the analytics side of a PostHog experiment — exposure criteria (default `$feature_flag_called` vs custom exposure events), primary and secondary metrics, the supported metric types (count, sum, ratio with `math` and `math_property`, retention with `retention_window_start` and `start_handling`), multivariate user handling ("Exclude" vs "First seen variant"), and how to read results once the experiment is live. Use when the user adds or edits a primary or secondary metric (e.g. "add a secondary metric tracking 'downloaded_file' per user"), sets up a ratio metric (e.g. "revenue from purchase_completed / pageviews"), sets up a retention metric (e.g. "$pageview → uploaded_file, 7-day window"), configures custom exposure (e.g. "only count users who hit /checkout"), changes multivariate handling, or asks "who is in the analysis?", "how do I measure impact?", "is this winning?", "what's the confidence level?", or "should I ship?".