checking-member-access
Explains what a member or a role can do in a PostHog project, using the access control MCP tools. Use when the user asks what someone can see or edit, who can…
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
$ npx -y skills add posthog/posthog --skill filtering-bot-traffic --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/filtering-bot-trafficContext preview
The summary Claude sees to decide when to auto-load this skill.
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
name: filtering-bot-traffic description: '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 $virt_* virtual properties). Use when the user asks to "exclude bots", "filter out crawlers", "remove bot traffic from my numbers", "how much of my traffic is bots / AI crawlers", "is GPTBot / ChatGPT / Claude hitting my site", "break down traffic by human vs bot", or wants clean human-only counts in an insight or dashboard. For the real-time Live tab bot tiles, use exploring-live-traffic instead.'
PostHog classifies every request by user agent so you can tell humans apart from bots, crawlers, and AI agents anywhere HogQL runs — the SQL editor, insights, trends, and Web analytics breakdowns. This skill teaches you (the agent) how to use that classification to:
For real-time ("right now", last 30 min) bot questions and the Live tab tiles, use the **exploring-live-traffic** skill instead. This skill is for historical windows, saved insights, dashboards, and filtering.
Use it when the user wants to:
Do **not** use it for the Live tab, real-time numbers, or the per-minute bot charts — that is exploring-live-traffic.
Two equivalent ways to reach the same classification. Prefer **virtual properties** in the insight builder and filters; use **functions** in hand-written SQL or when you need a value the virtual properties don't expose.
These read the user agent for you (falling back from `$raw_user_agent` to `$user_agent`), so you don't pass anything in. Available wherever you pick an event property.
| Property | Value | | ------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `$virt_is_bot` | boolean — `true` for bots / crawlers / automation | | `$virt_traffic_type` | `Regular`, `AI Agent`, `Bot`, or `Automation` | | `$virt_traffic_category` | finer category, e.g. `ai_crawler`, `ai_search`, `ai_assistant`, `search_crawler`, `seo_crawler`, `social_crawler`, `monitoring`, `http_client`, `headless_browser`, `no_user_agent`, `regular` | | `$virt_bot_name` | display name, e.g. `Googlebot`, `GPTBot`, `ClaudeBot` | | `$virt_bot_operator` | company behind the bot, e.g. `Google`, `OpenAI`, `Anthropic` |
Pass the user agent explicitly. Use `coalesce(nullIf(properties.$raw_user_agent, ''), properties.$user_agent)` to cover both server-side (`$raw_user_agent`) and JS SDK (`$user_agent`) captures. The `nullIf` keeps an empty `$raw_user_agent` from shadowing a real `$user_agent` and being misread as a bot — this mirrors the expression the virtual properties use internally.
| Function | Returns | | ------------------------ | ---------------------------------------------------------------------------- | | `isLikelyBot(ua)` | `true` if the UA matches a bot/automation pattern (empty UA counts as a bot) | | `getTrafficType(ua)` | `AI Agent` / `Bot` / `Automation` / `Regular` | | `getTrafficCategory(ua)` | subcategory; `regular` for humans | | `getBotType(ua)` | same subcategory but empty string for humans — handy for filtering | | `getBotName(ua)` | bot name; empty for humans | | `getBotOperator(ua)` | operator/company; empty for humans |
`getTrafficType` / `$virt_traffic_type` sorts every request into four buckets. The default move differs per bucket — don't treat them all as noise:
| Type | What it is | Default move | | ------------ | --------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------- | | `Regular` | Human visitors
:hedgehog: PostHog is the leading platform for building self-driving products. Our developer tools – AI observability, analytics, session replay, flags, experiments, error tracking, logs, and more – capture all the context agents need to diagnose problems, uncover opportunities, and ship fixes. Steer it all from Slack, web, desktop, or the MCP.
Repo: posthog/posthog
Explains what a member or a role can do in a PostHog project, using the access control MCP tools. Use when the user asks what someone can see or edit, who can…
Analyze the most expensive users in AI observability and explain why they cost so much. Use when the user asks about top spenders, expensive users, per-user…
Author continuously-running online evaluations in PostHog AI observability, grounded in real failure modes you've identified. Use when the user wants…
Find where an AI/LLM application is failing in production and surface the failure patterns, working from real traces. Use when someone wants to understand…
Investigate AI observability clusters — understand usage patterns in AI/LLM traffic, compare cluster behavior, compute cost/latency metrics, and drill into…
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…