Agent Skills

exploring-live-traffic

★ 35,336

by posthog

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. Use when the user asks "who is on my site right now?", "what is happening live?", "what bots are crawling me?", asks about the "live tab" / "live dashboard", wants live numbers (last 30 min), or wants help filtering or drilling into the live view. Also covers building product-analytics insights that m

🧰 Not standalone — use together with posthog/posthog

exploring-llm-clusters

★ 35,336

by posthog

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.

🧰 Not standalone — use together with posthog/posthog

exploring-llm-costs

★ 35,336

by posthog

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.

🧰 Not standalone — use together with posthog/posthog

exploring-llm-traces

★ 35,336

by posthog

ABSOLUTE MUST to debug and inspect LLM/AI agent traces using PostHog's MCP tools. Use when the user pastes a trace or session URL (e.g. /ai-observability/traces/<id> or /ai-observability/sessions/<id>), asks to debug a trace, figure out what went wrong, check if an agent used a tool correctly, verify context/files were surfaced, inspect subagent behavior, investigate LLM decisions, or analyze token usage and costs. Also use when raw SQL/HogQL against `events.properties.$ai_input` / `$ai_output_c

🧰 Not standalone — use together with posthog/posthog

exploring-mcp-intent-clusters

★ 35,336

by posthog

Explore PostHog MCP intent clusters — agent goals grouped by semantic similarity, with each cluster's tool distribution and error rates. 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?", wants to recompute the clustering, or pastes an MCP analytics intent-clustering URL.

🧰 Not standalone — use together with posthog/posthog

exploring-mcp-sessions

★ 35,336

by posthog

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?", or pastes an MCP analytics sessions URL.

🧰 Not standalone — use together with posthog/posthog

exploring-mcp-tool-quality

★ 35,336

by posthog

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.

🧰 Not standalone — use together with posthog/posthog

exploring-mcp-tool-usage

★ 35,336

by posthog

Starting point for exploring how a PostHog MCP server's tools are used — routes a broad question to the typed tool that answers it. Use when the user asks "how is my MCP doing?", "what should I look at?", "explore my tool calls", "who uses my MCP tools?", "what are agents doing with the MCP?", or pastes an MCP analytics URL without a specific question. Offers a menu of questions, each backed by a query tool, then hands off to the focused skill.

🧰 Not standalone — use together with posthog/posthog

exploring-replay-vision-observations

★ 35,336

by posthog

Guides agents through pulling a Replay Vision scanner's observations, reading the findings, and acting on them — summarizing patterns across sessions, drilling into individual recordings, and turning real, corroborated issues into PostHog tasks, insights, or an investigating-replay hand-off.\nTRIGGER when: user wants to pull/read/triage Replay Vision observations, asks \"what has my scanner found\", wants to act on or summarize scanner findings, turn observations into tasks/work, or points at a

🧰 Not standalone — use together with posthog/posthog

exploring-scouts

★ 35,336

by posthog

How to explore and make sense of PostHog Signals scouts — the scheduled agents that scan a project and write reports into the Signals inbox. Use when a user wants to understand what scouts they have, how each one is behaving, and whether the fleet is actually working. Covers surveying the fleet and its schedules, reading recent scout runs and drilling into a single run's reasoning, inspecting the durable scratchpad memory the fleet has built up, tracing a run to the reports it wrote or edited, a

🧰 Not standalone — use together with posthog/posthog

feature-usage-feed

★ 35,336

by posthog

Set up an LLM-judge evaluation that extracts canonical use cases for a PostHog feature at scale and streams the results to a Slack channel as a live feed. Use when someone wants to understand how users are actually using a specific AI/LLM-powered feature in production — what they're investigating, what questions they're trying to answer, and what patterns surface — without manually reading hundreds of traces. Assumes the feature emits `$ai_generation` and `$ai_evaluation` events with `$session_i

🧰 Not standalone — use together with posthog/posthog

filtering-bot-traffic

★ 35,336

by posthog

Identify, measure, and exclude bot / crawler / AI-agent traffic in PostHog web and product analytics using the traffic classification surface (the isLikelyBot / getTrafficType HogQL functions and the $virt_* virtual properties). Use when the user asks to "exclude bots", "filter out crawlers", "remove bot traffic from my numbers", "how much of my traffic is bots / AI crawlers", "is GPTBot / ChatGPT / Claude hitting my site", "break down traffic by human vs bot", or wants clean human-only counts i

🧰 Not standalone — use together with posthog/posthog

finding-deleted-feature-flags

★ 35,336

by posthog

Find feature flags that were soft-deleted in the active project within a recent time window. Use when the user asks "what flags were deleted in the last N days", "show me recently deleted feature flags", "who deleted flag X", "audit recent flag deletions", or anything similar. Handles the non-obvious gotcha that system.feature_flags exposes the deleted boolean but does not expose a deletion timestamp — the actual deleted-at time lives in the per-flag activity log and must be cross-referenced.

🧰 Not standalone — use together with posthog/posthog

finding-replay-for-issue

★ 35,336

by posthog

Finds the most informative session recording linked to an error tracking issue. Use when a user has an error tracking issue ID and wants to watch a replay showing what the user was doing when the error occurred. Ranks linked sessions by recency, activity score, and journey completeness, then summarizes the pre-error context. Replaces blind session picking from potentially hundreds of linked recordings.

🧰 Not standalone — use together with posthog/posthog

finding-sessions-to-watch

★ 35,336

by posthog

Guides a user from "I want to watch recordings but don't know which ones" to a short, high-signal list of sessions worth watching. Use when the user asks which sessions or replays to watch, wants help finding interesting / useful recordings, says they don't know where to start in session replay, or wants to watch sessions about a goal (signup, pricing, onboarding, checkout, a feature, rageclicks, errors, mobile, a specific person) without naming exact filters. Turns a vague intent into a focused

🧰 Not standalone — use together with posthog/posthog

fixing-flaky-tests

★ 35,336

by posthog

Guides an agent through reproducing, root-causing, fixing, and validating flaky tests in the PostHog monorepo. Use when a test fails intermittently in CI but passes on rerun or locally, when `hogli ci:insights` or the debugging-ci-failures skill classifies a failure as a flaky test, when given a GitHub Actions URL for a flaky job, or when asked to deflake, stabilize, or fix a flaky Jest, pytest, or Playwright test. Core discipline: reproduce locally before changing anything, fix the root cause (

🧰 Not standalone — use together with posthog/posthog

formatting-insight-axes

★ 35,336

by posthog

Pick the right y-axis unit when creating or updating a TrendsQuery insight via `posthog:insight-create` or `posthog:insight-update`. Use when the agent is about to add a `formula` purely to convert units (e.g. dividing seconds by 60 to display minutes), when a `math_property` is a duration, currency, ratio, or large count, or whenever the user mentions "format the y-axis", "duration", "seconds", "minutes", "hours", "milliseconds", "ms", "percentage", "currency", "decimals", "axis label", or "axi

🧰 Not standalone — use together with posthog/posthog

generating-clickhouse-query-performance-reports

★ 35,336

by posthog

Produce and structure slow-query performance reports for PostHog's production ClickHouse (US and EU). Use when asked for a slow query report, query performance analysis over the last N days, per-team query cost, OOM or timeout investigation, cluster cost/memory regressions, or materialization candidates. Covers the modern `query_log_archive` source (typed `lc_*` columns, multi-day retention), how to categorize and attribute slow queries, root-cause patterns (unmaterialized JSONExtract, high-card

🧰 Not standalone — use together with posthog/posthog

grouping-noisy-errors

★ 35,336

by posthog

Consolidate PostHog error tracking issues that are the same actual error reported under different fingerprints. Use when the user asks "why do I have so many TypeError issues that look the same?", "merge these duplicates", "stop splitting this error into new issues", or wants to clean up fingerprint sprawl. Decides between a one-shot merge of existing issues and a durable grouping rule that keeps future events from creating new fingerprints. Does NOT group conceptually similar bugs across differ

🧰 Not standalone — use together with posthog/posthog

improving-mcp-tools

★ 35,336

by posthog

Run an improve-my-MCP campaign: an autoresearch-style loop that measures the MCP agent experience with the eval harness, picks the highest-impact tool problem from production data, makes one bounded fix, and keeps it only if before/after scores improve. Use when asked to "improve my MCP", run an MCP improvement campaign, fix tool discoverability or descriptions based on evidence, or prepare an eval-backed PR for a tool change. Every shipped change must carry eval evidence; guardrails below are h

🧰 Not standalone — use together with posthog/posthog

inbox-exploration

★ 35,336

by posthog

Explore PostHog's Inbox and act on what it surfaces — the place where signal reports cluster into actionable issues and trends. Use when the user asks "what's in my inbox?", "what should I look at?", "which reports are actionable?", "what's PostHog flagged recently?", asks about a specific report by ID or title, wants to act on / fix / implement a report (turn it into a PR), wants to dismiss or snooze a report, or wants to see which signal sources are configured. Covers listing, filtering, drill

🧰 Not standalone — use together with posthog/posthog

incident-io-playbook

★ 35,336

by posthog

How to work incident.io through its connected MCP — list active incidents, fetch context for an incoming webhook, post triage updates, and (rare) open a new incident. Load when an incident.io webhook fires the agent, when an alert correlates to an active incident, or when recording a resolved outcome.

🧰 Not standalone — use together with posthog/posthog

investigate-metric

★ 35,336

by posthog

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.

🧰 Not standalone — use together with posthog/posthog

investigating-error-issue

★ 35,336

by posthog

Investigates a single PostHog error tracking issue end-to-end. Use when the user provides an issue ID or pastes an issue URL (`/error_tracking/<id>`) and wants to understand the error — who it affects, what triggers it, when it started, whether it correlates with a release, browser, OS, or feature flag, and what the next step should be. Pulls aggregated metrics, sample exception events, segment breakdowns, linked replays, and synthesizes a hypothesis-grade summary in one pass.

🧰 Not standalone — use together with posthog/posthog

investigating-metric-anomalies

★ 35,336

by posthog

Investigates server/infrastructure metric anomalies in PostHog Metrics — from "this metric is rising/dropping/spiking" or a fired alert to a probable cause with evidence. Use when asked why a metric looks wrong (ingestion lag rising, error rate spiking, latency degrading, queue depth growing, throughput dropping), when an alert fires on an OTel/Prometheus metric, or for any incident triage that starts from a metric symptom. Composes characterize-metric-anomaly, query-metrics, and metric-names-li

🧰 Not standalone — use together with posthog/posthog

investigating-replay

★ 35,336

by posthog

Investigates a session recording by gathering metadata, person profile, same-session events, and linked error tracking issues in one pass. Use when a user provides a recording or session ID and wants to understand what happened — who the user was, what they did, what errors occurred, and whether there are related error tracking issues. Replaces the manual chain of session-recording-get, persons-retrieve, execute-sql, and query-error-tracking-issues-list.

🧰 Not standalone — use together with posthog/posthog

kudos-storage

★ 35,336

by posthog

The data model — the `kudos` table columns, the `kudos_id` dedupe/idempotency scheme, and the per-recipient `people/<handle>.md` profile memory. Load before any table-append or memory-write.

🧰 Not standalone — use together with posthog/posthog

manage-dashboard-widgets

★ 35,336

by posthog

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 confirm

🧰 Not standalone — use together with posthog/posthog

managing-experiment-lifecycle

★ 35,336

by posthog

Guides experiment state transitions: launching, pausing, resuming, ending, shipping variants, archiving, resetting, duplicating, and copying to another project. Covers preconditions, implications for variant assignment and analysis, and the decision framework for when to use each action.\nTRIGGER when: user asks to launch, pause, resume, end, ship, archive, reset, duplicate, or copy an experiment to another project.\nDO NOT TRIGGER when: user is creating an experiment (use creating-experiments),

🧰 Not standalone — use together with posthog/posthog

managing-github-actions-secrets

★ 35,336

by posthog

Creates and updates GitHub Actions secrets for PostHog workflows. Use when adding a new CI secret, rotating an existing secret, wiring a workflow to an API token, package registry credential, deploy key, or any value referenced via `${{ secrets.* }}` in `.github/workflows/`.

🧰 Not standalone — use together with posthog/posthog