A short, design-led motion graphic where motion is the message — kinetic typography, stat count-up, chart/data-viz hit, logo sting / brand lockup, lower-third / callout / social overlay, animated map (highlight regions, connect places, zoom to a location), animated tweet / news-article / headline, webpage / UI animation (scroll, cursor, callouts), or fusing a real image's geometry into a chart. Usually under 10s (up to ~30s), no narration or live-action subject; renders to MP4 or transparent overlay. Longer / narrated / multi-scene → /general-video. Unclear → /hyperframes.

Mandatory entry point: read this first for any request to make, create, edit, animate, or render a video, animation, or motion graphic, including a promo, explainer, captioned clip, title card, overlay, slideshow or interactive deck, Remotion port, or any HyperFrames HTML composition. Also use it to inspect, diagnose, validate, preview, publish, or batch-render an existing HyperFrames project. Inputs may be a website URL, GitHub PR, Figma design or URL, text or brief, existing footage, or music. It resumes project state, captures intent when applicable, selects and installs the owning workflow, and routes domain capabilities. HyperFrames is the default output framework unless the user explicitly chooses another framework for the deliverable or asks only to record a browser session.

Use the HyperFrames CLI development loop: init, add, catalog, capture, lint, check, snapshot, compare, grade-compare, preview, play, present, beats, keyframes, single or batch render, publish, cloud, cloudrun, feedback, lambda, doctor, browser, info, upgrade, skills, compositions, docs, benchmark, telemetry, transcribe, auth, tts, and remove-background. Also use when diagnosing build or render failures. validate, inspect, and layout are deprecated aliases; use check. Covers local, HeyGen-hosted cloud, AWS Lambda, and Google Cloud Run rendering.

Diagnose why a product metric changed (dropped, spiked, or plateaued) by orchestrating breakdowns, actors, paths, lifecycle, retention, and annotations queries. Use when the user reports an anomaly, asks "why did X change?", or needs root-cause analysis for a trend, funnel, retention, stickiness, or lifecycle metric.

Required reading before writing any HogQL/SQL or calling execute-sql against PostHog. Use whenever the user wants to search, find, or do complex aggregations PostHog entities (insights, dashboards, cohorts, feature flags, experiments, surveys, hog flows, data warehouse, persons, etc.) and query analytics data (trends, funnels, retention, lifecycle, paths, stickiness, web analytics, error tracking, logs, sessions, LLM traces). Also the first stop for a governed business number (MRR, activation, revenue): check the semantic layer (canonical metrics in system.information_schema.metrics) for an approved definition before deriving from raw events. Covers HogQL syntax differences from ClickHouse SQL, system table schemas (system.*), available functions, query examples, and the schema-discovery workflow.

Investigate the quality of PostHog MCP tool calls — error rates, latency, reach, and which tools are failing or slow. Use when the user asks "which MCP tool has the highest error rate?", "what's the slowest tool?", "which tools fail most often?", "how reliable is tool X?", wants a tool-quality matrix, or pastes an MCP analytics tool-quality / dashboard URL and asks what it shows.

Investigate individual PostHog MCP sessions — the sequence of tool calls a single agent made in one run, what it was trying to do, and where it went wrong. Use when the user asks "what did this MCP session do?", "show me the tool calls for session X", "what was the agent's goal?", "which sessions had errors?", "who is connecting to my MCP?", or pastes an MCP analytics sessions URL.

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, description fit, tool overlaps). Use when the user asks "what are agents trying to do with the MCP?", "group the intents", "which goals fail most?", "what does each cluster route to?", "when agents have this intent do they find my tool?", "which tools get mixed up?", wants to recompute the clustering, or pastes an MCP analytics intent-clustering URL.

Diagnoses and resolves PostHog ingestion warnings — problems recorded while ingesting events (dropped events, rejected person merges, oversized payloads, invalid data). Use when a user asks why events are missing, dropped, or undercounted, why identify/alias calls don't work or accounts stay duplicated, why person or group properties aren't updating or profiles look inflated, why recordings have gaps, heatmaps are empty, LLM token counts are missing, why cookieless events vanish, or whenever the `ingestion_warning` health check fires. Explains severity triage (error = dropped, warning = modified, info = intentional) and routes all warning types — size limits and enrichment, merges and distinct IDs, `$process_person_profile`, timestamps, cookieless, heatmaps, transformations, session replay — to per-issue reference files with code-level causes and per-SDK fixes.

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, Bayesian vs Frequentist), PostHog-vs-SQL discrepancies, surprises after mid-run edits, and qualitative follow-up via a variant-split survey. TRIGGER when: user asks 'is my experiment biased?' or 'why 0 exposures?', references the bias banner, says a variant looks strange / wrong / off, sees significance flipping or A/A significance, finds PostHog numbers disagreeing with their SQL, reports surprises after mid-run edits, or wants qualitative feedback or a survey for an experiment. DO NOT TRIGGER when: creating an experiment (use creating-experiments), only configuring rollout (use configuring-experiment-rollout) or metrics (use configuring-experiment-analytics), or only asking lifecycle questions (use managing-experiment-lifecycle).

Connect a real Slack workspace to local PostHog Conversations (the SupportHog Slack app) so Slack messages become support tickets and replies post back. Use when the user wants to test the conversations Slack integration locally, hits "Support Slack OAuth client ID is not configured", gets a white screen or "Network error" on the OAuth callback, or asks how to set SUPPORT_SLACK_APP_CLIENT_ID / a tunnel for supporthog Slack events. Covers the Slack app + scopes, the SUPPORT_SLACK_* dynamic settings, and the key split: localhost for OAuth and the UI, a public tunnel only for inbound events.

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. Use when the user asks "how much are we spending on LLMs?", "which model / user / feature is most expensive?", "why did cost spike?", wants to build a cost dashboard or alert, or pastes a trace URL and asks about its cost.

Guide for writing or reviewing PostHog kea logic files (`*Logic.ts` / `*Logic.tsx`). Use when creating a new logic, adding actions/reducers/selectors/listeners/loaders/forms/router bindings, choosing between reducer vs selector vs cache, deciding between listeners and `kea-subscriptions`, wiring React with `useValues`/`useActions`/`BindLogic`, or onboarding to kea conventions. Read keajs.org for upstream API; this skill captures PostHog-specific conventions and idioms.

Teaches how to write and run evals on the `products/posthog_ai/eval_harness/` harness — sandboxed agent suites that execute the real coding agent in a Docker or Modal sandbox against a seeded Hedgebox project, and one-shot suites that score a single in-process model invocation per case. Use when adding or changing eval suites, cases, scorers, seeders, or synthesizers under `products/posthog_ai/evals/` or `products/*/evals/`, when touching the harness under `products/posthog_ai/eval_harness/`, or when running or debugging those evals (`hogli evals`). Covers suite kinds and discovery, case anatomy, the seeder/synthesizer split, the one-branch scorer patterns, and how to read results. Not for `ee/hogai/eval/ci/` pytest evals, and not for the LLM Analytics product's evaluation features.

Guides PostHog engineers through dashboard widget platform work — ship a new widget_type (WIDGET_REGISTRY, catalog, run_widgets, WidgetCard) or update a shipped type (config, query, layout, RBAC, tile filter bar, list footer, titleHref, throttles). Use for WidgetSpec, widget_specs/, widget-configs.zod.ts, hogli build:openapi, error_tracking_list, session_replay_list, widgetFilters, formatWidgetListCountFooter, widget_query_throttle, or WidgetCard composition. New types need widget-intake confirmation first. Not for MCP batch-add of existing types or adding tiles to a dashboard.

Guide for exposing PostHog product endpoints as MCP tools. Use when creating new or updating API endpoints, adding MCP tool definitions, scaffolding YAML configs, or writing serializers with good descriptions. Covers the full pipeline from Django serializer to generated TypeScript tool handler.

Trigger Novu notification workflows to send messages across email, SMS, push, chat, and in-app channels. Supports single triggers, bulk triggers, broadcast to all subscribers, topic-based targeting, and cancellation. Use when sending transactional notifications, alerts, or any event-driven messages.

Design notification workflows the Novu way — choose channels, set severity, decide when a workflow is critical, configure digests, and route based on subscriber state. Applies to BOTH dashboard-authored and code-first (`@novu/framework`) workflows. Use when planning a new workflow, deciding which channels to include, picking severity, configuring digest behavior, or matching a use case (order confirmation, payment failed, account suspended, comment, trial expiring, password reset, webhook fan-out, fetch-then-notify) to a proven template.

Git worktree command reference: path naming, create/remove/prune, `.env*` copy, package-manager install, and cleanup. Use when implementing or debugging worktree setup — not as the primary user-facing workflow (see nv-worktree-create).

Post-implementation PR prep for Novu feature branches — quality passes, commit/PR hygiene, CI triage, and review feedback. Use after feature work is done, when the user asks to prepare a PR, ship a branch, fix CI, address review comments, or babysit a pull request before merge.