PostHog skills collection

Planning Voice Agent User Interviews

Plan a round of user interviews conducted by PostHog's AI voice agent (a "robo interviewer") — the automated voice-agent interview product. Captures a UserInterviewTopic (who to target, what to ask, framing context, question list) and…

Querying Canvas Data

Get PostHog data into a canvas correctly: the host-injected ph SDK (loadInsight, query, capture, state, connectors, openExternal, navigate), the data hierarchy (saved insights first, typed query nodes second, inline HogQL last)…

Querying Posthog Data

Explains how to choose typed queries or SQL for PostHog data. Read it before you write HogQL/SQL. Also read it before you call execute-sql against PostHog. Use it to find or aggregate PostHog entities. These entities include insights…

Resolving Ingestion Warnings

Diagnoses and resolves PostHog ingestion warnings — problems recorded while ingesting events (dropped events, rejected person merges, oversized payloads, invalid data).

Review Hog Authoring

How to author custom PostHog Review skills: the review perspectives, blind-spot checks, validation criteria, and resolution criteria that drive PostHog Review's automated PR reviews.

Review Hog Blind Spots General

The general blind-spot check for PostHog Review, the final sweep that runs after every enabled review perspective has reviewed a chunk. Hunts for real, high-value issues that ALL of the perspectives missed, conditioned on what they…

Review Hog Perspective Contracts Security

The Contracts & Security review perspective for PostHog Review. Verifies that changed code is safe and maintains compatibility: API contracts and breaking changes, injection / authz / data exposure, input validation, and schema /…

Review Hog Perspective Logic Correctness

The Logic & Correctness review perspective for PostHog Review. Verifies that changed code does what it is supposed to do: business logic, edge cases, data transformations, and query / data-access correctness. Reports correctness issues…

Review Hog Perspective Performance Reliability

The Performance & Reliability review perspective for PostHog Review. Verifies that changed code will perform and hold up in production: resource efficiency, error handling and recovery, scalability, and operational readiness. Reports…

Review Hog Resolution Criteria

The resolution criteria for PostHog Review's resolution stage: the bar for deciding, per unresolved review thread, whether the ask is worth implementing and safe to implement unattended. Implements contained, provable fixes; declines…

Review Hog Validation Criteria

The validation criteria for PostHog Review, the bar for deciding whether a flagged PR issue is worth keeping. Keeps real, user-affecting correctness / security / data-loss / contract / performance problems; drops overengineering…

Scanning Experiments With Replay Vision

Provisions a Replay Vision scanner scoped to one experiment's exposed sessions: sets experimenttargeting so the API derives the person-scoped exposure filter server-side, templates a prompt that stays comparable across variants, sizes…

Setting Up A Custom Rest Source

Connect an arbitrary REST API to the PostHog data warehouse as a Custom source by authoring a JSON manifest, with no per-source code.

Setting Up A Data Warehouse Source

Guide the user through connecting a new data warehouse source — Postgres, MySQL, Stripe, Hubspot, MongoDB, Salesforce, BigQuery, Snowflake, and so on.

Setting Up Data Catalog

Populates and maintains a project's data catalog (semantic layer): canonical metrics, trust marks (certifications) on warehouse tables/views, and reviewed table relationships.

Setting Up Warehouse Properties

Populate person or group properties from a data warehouse table or materialized view, so warehouse columns become properties usable in feature flags, cohorts, and insights.

Signals

How to query the documentembeddings table for raw signal data using HogQL.

Signals Scout AI Observability

Signals scout for PostHog AI observability. Watches LLM traces for cost, latency, error, volume, and eval-performance regressions.

Signals Scout Anomaly Detection

Signals scout that watches the project's most-viewed dashboards and insights for anomalies — bursts, drops, flat-lines, and trend breaks — against each insight's own seasonality-matched baseline.

Signals Scout Apm

Signals scout for PostHog distributed tracing (APM / OpenTelemetry spans). Watches per-service RED metrics for error-rate and latency regressions, new error signatures, and traffic cliffs.