[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-posthog-querying-canvas-data":3,"mdc--ftlj5u-key":48,"related-repo-posthog-querying-canvas-data":616,"related-org-posthog-querying-canvas-data":719},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":23,"repoUrl":24,"updatedAt":25,"license":26,"forks":27,"topics":28,"repo":43,"sourceUrl":46,"mdContent":47},"querying-canvas-data","query and load PostHog canvas data","Get PostHog data into a canvas correctly: the host-injected `ph` SDK (loadInsight, query, capture, openExternal, navigate), the data hierarchy (saved insights first, typed query nodes second, inline HogQL last), per-insight-type result shapes, date-range wiring, and event capture from a canvas. Use whenever a canvas shows metrics, charts, tables, or any PostHog data, or needs to send analytics events.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"posthog","PostHog","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fposthog.png",[12,14,17,20],{"name":9,"slug":8,"type":13},"tag",{"name":15,"slug":16,"type":13},"Data Analysis","data-analysis",{"name":18,"slug":19,"type":13},"Analytics","analytics",{"name":21,"slug":22,"type":13},"SDK","sdk",35568,"https:\u002F\u002Fgithub.com\u002FPostHog\u002Fposthog","2026-08-06T06:09:16.504412",null,2977,[29,30,19,31,32,33,34,35,36,37,38,39,40,41,42],"ab-testing","ai-analytics","cdp","data-warehouse","experiments","feature-flags","javascript","product-analytics","python","react","session-replay","surveys","typescript","web-analytics",{"repoUrl":24,"stars":23,"forks":27,"topics":44,"description":45},[29,30,19,31,32,33,34,35,36,37,38,39,40,41,42],"🦔 PostHog is an all-in-one developer platform for building successful products. We offer product analytics, web analytics, session replay, error tracking, feature flags, experimentation, surveys, data warehouse, a CDP, and an AI product assistant to help debug your code, ship features faster, and keep all your usage and customer data in one stack.","https:\u002F\u002Fgithub.com\u002FPostHog\u002Fposthog\u002Ftree\u002FHEAD\u002Fproducts\u002Fcanvas\u002Fskills\u002Fquerying-canvas-data","---\nname: querying-canvas-data\ndescription: >\n  Get PostHog data into a canvas correctly: the host-injected `ph` SDK (loadInsight, query,\n  capture, openExternal, navigate), the data hierarchy (saved insights first, typed query nodes\n  second, inline HogQL last), per-insight-type result shapes, date-range wiring, and event capture\n  from a canvas. Use whenever a canvas shows metrics, charts, tables, or any PostHog data, or\n  needs to send analytics events.\n---\n\n# Querying canvas data\n\nThe global `ph` object (injected by the host — never imported, never initialized) is the only way\na canvas talks to PostHog. Credentials stay in the host; `fetch()`, posthog-js, and hand-rolled\nclients fail in the sandbox.\n\n## Data hierarchy — back every metric with a saved insight\n\n1. **Preferred — save an insight, load it by reference.** Use the PostHog MCP insight tools to\n   create\u002Fsave an insight that computes the metric with an insight query type (TrendsQuery,\n   FunnelsQuery, RetentionQuery, PathsQuery, or the web-analytics kinds WebOverviewQuery \u002F\n   WebStatsTableQuery — not raw SQL). Confirm its numbers, note the `short_id`, and render it with\n   `await ph.loadInsight(shortId, { dateRange })`. These are proven queries — numbers match the\n   PostHog UI exactly (sessionization, unique users, breakdowns, bounce rate). Never fabricate a\n   query or guess event\u002Fproperty names; discover and save them via MCP first.\n2. **Secondary — an ad-hoc typed node**: `ph.query({ kind: \"TrendsQuery\", series: [...], dateRange: {...} })`\n   when saving an insight genuinely doesn't fit.\n3. **Last resort — inline HogQL**: `ph.query(\"SELECT …\")`, only when no insight kind can express\n   the metric; you then own the SQL and its date window.\n\nFor web-analytics boards specifically, use the web-analytics query kinds — raw HogQL subtly gets\nbounce rate, sessionization, channel attribution, and unique-visitor counts wrong.\n\nWhatever tier you use, **declare it in the project's `capabilities`** before publishing: every\n`ph.loadInsight` short id in `capabilities.posthog.insights`, every `ph.capture` event name in\n`captureEvents`, and `inlineQueries: true` for any `ph.query` use. The host rejects undeclared\ncalls at runtime, and validation fails on undeclared literals.\n\n## Result shapes — read them correctly or every value renders 0\n\n- **Trends-style results** (insight query types, via `ph.loadInsight` or a typed node): `results`\n  is an array of **series objects**, not rows. Each series has `data: number[]` (per interval),\n  `days: string[]` (ISO), `labels: string[]`, `count` (sum), `aggregated_value` (single-value\n  total), `label`, and optional `compare_label: \"current\" | \"previous\"`. A KPI total is\n  `results[0].count` (or `.aggregated_value`); a line chart plots `results[0].data` over\n  `results[0].days`. With a compare period, find the prior series by `compare_label === \"previous\"`\n  — never by index. `columns` is empty here.\n- **SQL results**: `{ columns: string[], results: rows[][] }` — each row an array of cell values in\n  `columns` order.\n\nLoad data in `useEffect` with `useState`, show a loading state, and aggregate in the query; never\nfetch raw event dumps. Treat a rejected query and an empty result as different states: `.catch`\nmust set an error state that renders visibly (message + retry), never fall through to zeros, an\nempty chart, or a \"no data\" message — a swallowed error makes real breakage (a missing table, an\nauth failure) look like missing data. Reserve the empty state for a query that succeeded with no\nrows.\n\n## Date windows\n\n- Pass the canvas's date-picker window straight into `dateRange`:\n  `ph.loadInsight(shortId, { dateRange: { date_from: win.start.toISOString(), date_to: win.end.toISOString() } })`\n  — the saved insight re-scopes to the window with no time SQL. Typed nodes take the same\n  `dateRange`. Re-run every query when the window changes.\n- A saved **SQL** insight may ignore `dateRange` (its window lives inside the SQL) — a reason to\n  prefer insight query types.\n- Inline HogQL escape hatch only: never bake `now()` or a hardcoded INTERVAL. Compute unix bounds\n  (`Math.floor(win.start.getTime() \u002F 1000)`) and write half-open\n  `timestamp >= toDateTime(fromUnix) AND timestamp \u003C toDateTime(toUnix)`. Prior period = the\n  equal-length window immediately before; bucket with `toStartOfDay`\u002F`toStartOfHour`.\n\n## Side effects\n\n- `ph.capture(event, properties?, distinctId?)` — analytics events for interactions\n  (fire-and-forget). Session replay, `$session_id`, and person attribution are handled by the\n  host automatically; never roll your own capture.\n- `ph.openExternal(url)` — opens `https:\u002F\u002Fposthog.com` \u002F `*.posthog.com` URLs only, and only from\n  a user interaction (opens outside focus are ignored). Don't link elsewhere.\n- `ph.navigate.toTask(id)` \u002F `.toNewTask()` \u002F `.toCanvas(id)` \u002F `.toNewCanvas()` — in-app\n  navigation within the canvas's own channel.\n",{"data":49,"body":50},{"name":4,"description":6},{"type":51,"children":52},"root",[53,61,84,91,158,163,229,235,399,428,434,529,535],{"type":54,"tag":55,"props":56,"children":57},"element","h1",{"id":4},[58],{"type":59,"value":60},"text","Querying canvas data",{"type":54,"tag":62,"props":63,"children":64},"p",{},[65,67,74,76,82],{"type":59,"value":66},"The global ",{"type":54,"tag":68,"props":69,"children":71},"code",{"className":70},[],[72],{"type":59,"value":73},"ph",{"type":59,"value":75}," object (injected by the host — never imported, never initialized) is the only way\na canvas talks to PostHog. Credentials stay in the host; ",{"type":54,"tag":68,"props":77,"children":79},{"className":78},[],[80],{"type":59,"value":81},"fetch()",{"type":59,"value":83},", posthog-js, and hand-rolled\nclients fail in the sandbox.",{"type":54,"tag":85,"props":86,"children":88},"h2",{"id":87},"data-hierarchy-back-every-metric-with-a-saved-insight",[89],{"type":59,"value":90},"Data hierarchy — back every metric with a saved insight",{"type":54,"tag":92,"props":93,"children":94},"ol",{},[95,123,141],{"type":54,"tag":96,"props":97,"children":98},"li",{},[99,105,107,113,115,121],{"type":54,"tag":100,"props":101,"children":102},"strong",{},[103],{"type":59,"value":104},"Preferred — save an insight, load it by reference.",{"type":59,"value":106}," Use the PostHog MCP insight tools to\ncreate\u002Fsave an insight that computes the metric with an insight query type (TrendsQuery,\nFunnelsQuery, RetentionQuery, PathsQuery, or the web-analytics kinds WebOverviewQuery \u002F\nWebStatsTableQuery — not raw SQL). Confirm its numbers, note the ",{"type":54,"tag":68,"props":108,"children":110},{"className":109},[],[111],{"type":59,"value":112},"short_id",{"type":59,"value":114},", and render it with\n",{"type":54,"tag":68,"props":116,"children":118},{"className":117},[],[119],{"type":59,"value":120},"await ph.loadInsight(shortId, { dateRange })",{"type":59,"value":122},". These are proven queries — numbers match the\nPostHog UI exactly (sessionization, unique users, breakdowns, bounce rate). Never fabricate a\nquery or guess event\u002Fproperty names; discover and save them via MCP first.",{"type":54,"tag":96,"props":124,"children":125},{},[126,131,133,139],{"type":54,"tag":100,"props":127,"children":128},{},[129],{"type":59,"value":130},"Secondary — an ad-hoc typed node",{"type":59,"value":132},": ",{"type":54,"tag":68,"props":134,"children":136},{"className":135},[],[137],{"type":59,"value":138},"ph.query({ kind: \"TrendsQuery\", series: [...], dateRange: {...} })",{"type":59,"value":140},"\nwhen saving an insight genuinely doesn't fit.",{"type":54,"tag":96,"props":142,"children":143},{},[144,149,150,156],{"type":54,"tag":100,"props":145,"children":146},{},[147],{"type":59,"value":148},"Last resort — inline HogQL",{"type":59,"value":132},{"type":54,"tag":68,"props":151,"children":153},{"className":152},[],[154],{"type":59,"value":155},"ph.query(\"SELECT …\")",{"type":59,"value":157},", only when no insight kind can express\nthe metric; you then own the SQL and its date window.",{"type":54,"tag":62,"props":159,"children":160},{},[161],{"type":59,"value":162},"For web-analytics boards specifically, use the web-analytics query kinds — raw HogQL subtly gets\nbounce rate, sessionization, channel attribution, and unique-visitor counts wrong.",{"type":54,"tag":62,"props":164,"children":165},{},[166,168,179,181,187,189,195,197,203,205,211,213,219,221,227],{"type":59,"value":167},"Whatever tier you use, ",{"type":54,"tag":100,"props":169,"children":170},{},[171,173],{"type":59,"value":172},"declare it in the project's ",{"type":54,"tag":68,"props":174,"children":176},{"className":175},[],[177],{"type":59,"value":178},"capabilities",{"type":59,"value":180}," before publishing: every\n",{"type":54,"tag":68,"props":182,"children":184},{"className":183},[],[185],{"type":59,"value":186},"ph.loadInsight",{"type":59,"value":188}," short id in ",{"type":54,"tag":68,"props":190,"children":192},{"className":191},[],[193],{"type":59,"value":194},"capabilities.posthog.insights",{"type":59,"value":196},", every ",{"type":54,"tag":68,"props":198,"children":200},{"className":199},[],[201],{"type":59,"value":202},"ph.capture",{"type":59,"value":204}," event name in\n",{"type":54,"tag":68,"props":206,"children":208},{"className":207},[],[209],{"type":59,"value":210},"captureEvents",{"type":59,"value":212},", and ",{"type":54,"tag":68,"props":214,"children":216},{"className":215},[],[217],{"type":59,"value":218},"inlineQueries: true",{"type":59,"value":220}," for any ",{"type":54,"tag":68,"props":222,"children":224},{"className":223},[],[225],{"type":59,"value":226},"ph.query",{"type":59,"value":228}," use. The host rejects undeclared\ncalls at runtime, and validation fails on undeclared literals.",{"type":54,"tag":85,"props":230,"children":232},{"id":231},"result-shapes-read-them-correctly-or-every-value-renders-0",[233],{"type":59,"value":234},"Result shapes — read them correctly or every value renders 0",{"type":54,"tag":236,"props":237,"children":238},"ul",{},[239,375],{"type":54,"tag":96,"props":240,"children":241},{},[242,247,249,254,256,262,264,269,271,277,279,285,287,293,295,301,303,309,311,317,319,325,327,333,335,341,343,349,351,357,359,365,367,373],{"type":54,"tag":100,"props":243,"children":244},{},[245],{"type":59,"value":246},"Trends-style results",{"type":59,"value":248}," (insight query types, via ",{"type":54,"tag":68,"props":250,"children":252},{"className":251},[],[253],{"type":59,"value":186},{"type":59,"value":255}," or a typed node): ",{"type":54,"tag":68,"props":257,"children":259},{"className":258},[],[260],{"type":59,"value":261},"results",{"type":59,"value":263},"\nis an array of ",{"type":54,"tag":100,"props":265,"children":266},{},[267],{"type":59,"value":268},"series objects",{"type":59,"value":270},", not rows. Each series has ",{"type":54,"tag":68,"props":272,"children":274},{"className":273},[],[275],{"type":59,"value":276},"data: number[]",{"type":59,"value":278}," (per interval),\n",{"type":54,"tag":68,"props":280,"children":282},{"className":281},[],[283],{"type":59,"value":284},"days: string[]",{"type":59,"value":286}," (ISO), ",{"type":54,"tag":68,"props":288,"children":290},{"className":289},[],[291],{"type":59,"value":292},"labels: string[]",{"type":59,"value":294},", ",{"type":54,"tag":68,"props":296,"children":298},{"className":297},[],[299],{"type":59,"value":300},"count",{"type":59,"value":302}," (sum), ",{"type":54,"tag":68,"props":304,"children":306},{"className":305},[],[307],{"type":59,"value":308},"aggregated_value",{"type":59,"value":310}," (single-value\ntotal), ",{"type":54,"tag":68,"props":312,"children":314},{"className":313},[],[315],{"type":59,"value":316},"label",{"type":59,"value":318},", and optional ",{"type":54,"tag":68,"props":320,"children":322},{"className":321},[],[323],{"type":59,"value":324},"compare_label: \"current\" | \"previous\"",{"type":59,"value":326},". A KPI total is\n",{"type":54,"tag":68,"props":328,"children":330},{"className":329},[],[331],{"type":59,"value":332},"results[0].count",{"type":59,"value":334}," (or ",{"type":54,"tag":68,"props":336,"children":338},{"className":337},[],[339],{"type":59,"value":340},".aggregated_value",{"type":59,"value":342},"); a line chart plots ",{"type":54,"tag":68,"props":344,"children":346},{"className":345},[],[347],{"type":59,"value":348},"results[0].data",{"type":59,"value":350}," over\n",{"type":54,"tag":68,"props":352,"children":354},{"className":353},[],[355],{"type":59,"value":356},"results[0].days",{"type":59,"value":358},". With a compare period, find the prior series by ",{"type":54,"tag":68,"props":360,"children":362},{"className":361},[],[363],{"type":59,"value":364},"compare_label === \"previous\"",{"type":59,"value":366},"\n— never by index. ",{"type":54,"tag":68,"props":368,"children":370},{"className":369},[],[371],{"type":59,"value":372},"columns",{"type":59,"value":374}," is empty here.",{"type":54,"tag":96,"props":376,"children":377},{},[378,383,384,390,392,397],{"type":54,"tag":100,"props":379,"children":380},{},[381],{"type":59,"value":382},"SQL results",{"type":59,"value":132},{"type":54,"tag":68,"props":385,"children":387},{"className":386},[],[388],{"type":59,"value":389},"{ columns: string[], results: rows[][] }",{"type":59,"value":391}," — each row an array of cell values in\n",{"type":54,"tag":68,"props":393,"children":395},{"className":394},[],[396],{"type":59,"value":372},{"type":59,"value":398}," order.",{"type":54,"tag":62,"props":400,"children":401},{},[402,404,410,412,418,420,426],{"type":59,"value":403},"Load data in ",{"type":54,"tag":68,"props":405,"children":407},{"className":406},[],[408],{"type":59,"value":409},"useEffect",{"type":59,"value":411}," with ",{"type":54,"tag":68,"props":413,"children":415},{"className":414},[],[416],{"type":59,"value":417},"useState",{"type":59,"value":419},", show a loading state, and aggregate in the query; never\nfetch raw event dumps. Treat a rejected query and an empty result as different states: ",{"type":54,"tag":68,"props":421,"children":423},{"className":422},[],[424],{"type":59,"value":425},".catch",{"type":59,"value":427},"\nmust set an error state that renders visibly (message + retry), never fall through to zeros, an\nempty chart, or a \"no data\" message — a swallowed error makes real breakage (a missing table, an\nauth failure) look like missing data. Reserve the empty state for a query that succeeded with no\nrows.",{"type":54,"tag":85,"props":429,"children":431},{"id":430},"date-windows",[432],{"type":59,"value":433},"Date windows",{"type":54,"tag":236,"props":435,"children":436},{},[437,465,484],{"type":54,"tag":96,"props":438,"children":439},{},[440,442,448,450,456,458,463],{"type":59,"value":441},"Pass the canvas's date-picker window straight into ",{"type":54,"tag":68,"props":443,"children":445},{"className":444},[],[446],{"type":59,"value":447},"dateRange",{"type":59,"value":449},":\n",{"type":54,"tag":68,"props":451,"children":453},{"className":452},[],[454],{"type":59,"value":455},"ph.loadInsight(shortId, { dateRange: { date_from: win.start.toISOString(), date_to: win.end.toISOString() } })",{"type":59,"value":457},"\n— the saved insight re-scopes to the window with no time SQL. Typed nodes take the same\n",{"type":54,"tag":68,"props":459,"children":461},{"className":460},[],[462],{"type":59,"value":447},{"type":59,"value":464},". Re-run every query when the window changes.",{"type":54,"tag":96,"props":466,"children":467},{},[468,470,475,477,482],{"type":59,"value":469},"A saved ",{"type":54,"tag":100,"props":471,"children":472},{},[473],{"type":59,"value":474},"SQL",{"type":59,"value":476}," insight may ignore ",{"type":54,"tag":68,"props":478,"children":480},{"className":479},[],[481],{"type":59,"value":447},{"type":59,"value":483}," (its window lives inside the SQL) — a reason to\nprefer insight query types.",{"type":54,"tag":96,"props":485,"children":486},{},[487,489,495,497,503,505,511,513,519,521,527],{"type":59,"value":488},"Inline HogQL escape hatch only: never bake ",{"type":54,"tag":68,"props":490,"children":492},{"className":491},[],[493],{"type":59,"value":494},"now()",{"type":59,"value":496}," or a hardcoded INTERVAL. Compute unix bounds\n(",{"type":54,"tag":68,"props":498,"children":500},{"className":499},[],[501],{"type":59,"value":502},"Math.floor(win.start.getTime() \u002F 1000)",{"type":59,"value":504},") and write half-open\n",{"type":54,"tag":68,"props":506,"children":508},{"className":507},[],[509],{"type":59,"value":510},"timestamp >= toDateTime(fromUnix) AND timestamp \u003C toDateTime(toUnix)",{"type":59,"value":512},". Prior period = the\nequal-length window immediately before; bucket with ",{"type":54,"tag":68,"props":514,"children":516},{"className":515},[],[517],{"type":59,"value":518},"toStartOfDay",{"type":59,"value":520},"\u002F",{"type":54,"tag":68,"props":522,"children":524},{"className":523},[],[525],{"type":59,"value":526},"toStartOfHour",{"type":59,"value":528},".",{"type":54,"tag":85,"props":530,"children":532},{"id":531},"side-effects",[533],{"type":59,"value":534},"Side effects",{"type":54,"tag":236,"props":536,"children":537},{},[538,557,584],{"type":54,"tag":96,"props":539,"children":540},{},[541,547,549,555],{"type":54,"tag":68,"props":542,"children":544},{"className":543},[],[545],{"type":59,"value":546},"ph.capture(event, properties?, distinctId?)",{"type":59,"value":548}," — analytics events for interactions\n(fire-and-forget). Session replay, ",{"type":54,"tag":68,"props":550,"children":552},{"className":551},[],[553],{"type":59,"value":554},"$session_id",{"type":59,"value":556},", and person attribution are handled by the\nhost automatically; never roll your own capture.",{"type":54,"tag":96,"props":558,"children":559},{},[560,566,568,574,576,582],{"type":54,"tag":68,"props":561,"children":563},{"className":562},[],[564],{"type":59,"value":565},"ph.openExternal(url)",{"type":59,"value":567}," — opens ",{"type":54,"tag":68,"props":569,"children":571},{"className":570},[],[572],{"type":59,"value":573},"https:\u002F\u002Fposthog.com",{"type":59,"value":575}," \u002F ",{"type":54,"tag":68,"props":577,"children":579},{"className":578},[],[580],{"type":59,"value":581},"*.posthog.com",{"type":59,"value":583}," URLs only, and only from\na user interaction (opens outside focus are ignored). Don't link elsewhere.",{"type":54,"tag":96,"props":585,"children":586},{},[587,593,594,600,601,607,608,614],{"type":54,"tag":68,"props":588,"children":590},{"className":589},[],[591],{"type":59,"value":592},"ph.navigate.toTask(id)",{"type":59,"value":575},{"type":54,"tag":68,"props":595,"children":597},{"className":596},[],[598],{"type":59,"value":599},".toNewTask()",{"type":59,"value":575},{"type":54,"tag":68,"props":602,"children":604},{"className":603},[],[605],{"type":59,"value":606},".toCanvas(id)",{"type":59,"value":575},{"type":54,"tag":68,"props":609,"children":611},{"className":610},[],[612],{"type":59,"value":613},".toNewCanvas()",{"type":59,"value":615}," — in-app\nnavigation within the canvas's own channel.",{"items":617,"total":718},[618,633,645,657,670,685,701],{"slug":619,"name":619,"fn":620,"description":621,"org":622,"tags":623,"stars":23,"repoUrl":24,"updatedAt":632},"analyzing-expensive-users","analyze expensive users in AI observability","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 LLM cost, user-level cost drivers, or patterns behind high AI observability spend.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[624,625,628,631],{"name":18,"slug":19,"type":13},{"name":626,"slug":627,"type":13},"Cost Optimization","cost-optimization",{"name":629,"slug":630,"type":13},"Observability","observability",{"name":9,"slug":8,"type":13},"2026-07-28T05:34:11.117757",{"slug":634,"name":634,"fn":635,"description":636,"org":637,"tags":638,"stars":23,"repoUrl":24,"updatedAt":644},"auditing-endpoints","audit PostHog project endpoints","Audit every endpoint in a PostHog project for staleness, failed materialisations, and unused materialised versions. Use when the user asks \"what endpoints can I clean up?\", \"are any of my endpoints broken?\", \"which materialised versions are still being called?\", or wants a one-shot cleanup pass over the Endpoints product. Produces a prioritised report grouped by issue type, with recommended actions but does not modify anything without explicit confirmation.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[639,640,643],{"name":18,"slug":19,"type":13},{"name":641,"slug":642,"type":13},"Audit","audit",{"name":9,"slug":8,"type":13},"2026-06-08T08:08:33.693989",{"slug":646,"name":646,"fn":647,"description":648,"org":649,"tags":650,"stars":23,"repoUrl":24,"updatedAt":656},"auditing-warehouse-source-health","audit PostHog data warehouse source health","Audit the health of a PostHog project's data warehouse sources and syncs — find every broken or degraded source connection, sync schema, and webhook channel. Use when the user asks \"why are my imports failing?\", \"what's broken with my sources?\", \"why is my warehouse data stale?\", or wants a one-shot triage of source\u002Fsync health before deciding where to dig in. Produces a prioritized report grouped by severity, with recommended next steps. For materialized-view health use `auditing-warehouse-view-health`; for a single failing sync use `diagnosing-failed-warehouse-syncs`.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[651,652,654,655],{"name":641,"slug":642,"type":13},{"name":653,"slug":32,"type":13},"Data Warehouse",{"name":629,"slug":630,"type":13},{"name":9,"slug":8,"type":13},"2026-06-18T08:22:57.67984",{"slug":658,"name":658,"fn":659,"description":660,"org":661,"tags":662,"stars":23,"repoUrl":24,"updatedAt":669},"auditing-warehouse-view-health","audit PostHog materialized view health","Audit the health of a PostHog project's materialized views (saved queries) — find every failed materialization and flag unused or stale materialized views that cost storage and compute. Use when the user asks \"which of my views are broken?\", \"why is this materialized view failing?\", \"are any of my views wasting compute?\", or wants a one-shot triage of view health. For source\u002Fsync health use `auditing-warehouse-source-health`.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[663,664,665,668],{"name":641,"slug":642,"type":13},{"name":653,"slug":32,"type":13},{"name":666,"slug":667,"type":13},"Performance","performance",{"name":9,"slug":8,"type":13},"2026-06-18T08:25:10.936787",{"slug":671,"name":671,"fn":672,"description":673,"org":674,"tags":675,"stars":23,"repoUrl":24,"updatedAt":684},"authoring-error-tracking-alerts","author PostHog error tracking alerts","Author error tracking alerts that fire when an issue is created, reopened, or starts spiking. Use when the user asks to set up error notifications, route exceptions to Slack\u002Fwebhook\u002FLinear, or evaluate which error events are worth alerting on. Covers trigger-event selection, integration choice, dedup against existing alerts, and shipping with the canonical message body shape.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[676,679,682,683],{"name":677,"slug":678,"type":13},"Alerting","alerting",{"name":680,"slug":681,"type":13},"Debugging","debugging",{"name":629,"slug":630,"type":13},{"name":9,"slug":8,"type":13},"2026-06-18T08:24:40.318583",{"slug":686,"name":686,"fn":687,"description":688,"org":689,"tags":690,"stars":23,"repoUrl":24,"updatedAt":700},"authoring-log-alerts","author log alerts in PostHog","Author useful, low-noise log alerts on services in a PostHog project. Use when the user asks to set up alerts for their logs, suggest alerts they should add, or evaluate whether a service is worth monitoring. Covers service triage, baseline characterisation, threshold drafting, back-testing via simulate, and shipping with a notification destination.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[691,692,695,696,699],{"name":18,"slug":19,"type":13},{"name":693,"slug":694,"type":13},"Monitoring","monitoring",{"name":629,"slug":630,"type":13},{"name":697,"slug":698,"type":13},"Operations","operations",{"name":9,"slug":8,"type":13},"2026-07-18T05:10:54.430898",{"slug":702,"name":702,"fn":703,"description":704,"org":705,"tags":706,"stars":23,"repoUrl":24,"updatedAt":717},"building-canvases","create and edit PostHog canvases","Create or edit a PostHog canvas — a sandboxed browser application (data board, document, form, small tool, graphics experiment) stored in PostHog and rendered by the desktop\u002Fweb app. Use when a task asks to build, generate, update, or fix a canvas, or when a canvas id is given as the publish target. Covers resolving or creating the target canvas, choosing an implementation approach (React + Quill vs plain HTML\u002Fbrowser APIs), the read → edit → validate → publish → build loop, and which companion canvas skills to load for the details.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[707,710,713,714],{"name":708,"slug":709,"type":13},"Automation","automation",{"name":711,"slug":712,"type":13},"Design","design",{"name":9,"slug":8,"type":13},{"name":715,"slug":716,"type":13},"Prototyping","prototyping","2026-08-06T06:09:29.946969",74,{"items":720,"total":844},[721,728,734,741,748,755,763,770,788,804,819,831],{"slug":619,"name":619,"fn":620,"description":621,"org":722,"tags":723,"stars":23,"repoUrl":24,"updatedAt":632},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[724,725,726,727],{"name":18,"slug":19,"type":13},{"name":626,"slug":627,"type":13},{"name":629,"slug":630,"type":13},{"name":9,"slug":8,"type":13},{"slug":634,"name":634,"fn":635,"description":636,"org":729,"tags":730,"stars":23,"repoUrl":24,"updatedAt":644},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[731,732,733],{"name":18,"slug":19,"type":13},{"name":641,"slug":642,"type":13},{"name":9,"slug":8,"type":13},{"slug":646,"name":646,"fn":647,"description":648,"org":735,"tags":736,"stars":23,"repoUrl":24,"updatedAt":656},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[737,738,739,740],{"name":641,"slug":642,"type":13},{"name":653,"slug":32,"type":13},{"name":629,"slug":630,"type":13},{"name":9,"slug":8,"type":13},{"slug":658,"name":658,"fn":659,"description":660,"org":742,"tags":743,"stars":23,"repoUrl":24,"updatedAt":669},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[744,745,746,747],{"name":641,"slug":642,"type":13},{"name":653,"slug":32,"type":13},{"name":666,"slug":667,"type":13},{"name":9,"slug":8,"type":13},{"slug":671,"name":671,"fn":672,"description":673,"org":749,"tags":750,"stars":23,"repoUrl":24,"updatedAt":684},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[751,752,753,754],{"name":677,"slug":678,"type":13},{"name":680,"slug":681,"type":13},{"name":629,"slug":630,"type":13},{"name":9,"slug":8,"type":13},{"slug":686,"name":686,"fn":687,"description":688,"org":756,"tags":757,"stars":23,"repoUrl":24,"updatedAt":700},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[758,759,760,761,762],{"name":18,"slug":19,"type":13},{"name":693,"slug":694,"type":13},{"name":629,"slug":630,"type":13},{"name":697,"slug":698,"type":13},{"name":9,"slug":8,"type":13},{"slug":702,"name":702,"fn":703,"description":704,"org":764,"tags":765,"stars":23,"repoUrl":24,"updatedAt":717},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[766,767,768,769],{"name":708,"slug":709,"type":13},{"name":711,"slug":712,"type":13},{"name":9,"slug":8,"type":13},{"name":715,"slug":716,"type":13},{"slug":771,"name":771,"fn":772,"description":773,"org":774,"tags":775,"stars":23,"repoUrl":24,"updatedAt":787},"building-html-canvases","author HTML and CSS PostHog canvases","Author a PostHog canvas with semantic HTML, CSS, and direct browser APIs — documents, articles, generative graphics, 2D canvas and WebGL experiences, and focused experiments where React components add no useful structure. Use after building-canvases has routed a canvas request to a plain-HTML\u002Fbrowser-API implementation. Covers the thin component wrapper the current runtime requires, styling and theming without Quill, drawing surfaces, and animation\u002Fcleanup patterns.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[776,779,780,783,786],{"name":777,"slug":778,"type":13},"CSS","css",{"name":711,"slug":712,"type":13},{"name":781,"slug":782,"type":13},"Graphics","graphics",{"name":784,"slug":785,"type":13},"HTML","html",{"name":9,"slug":8,"type":13},"2026-08-06T06:09:30.313848",{"slug":789,"name":789,"fn":790,"description":791,"org":792,"tags":793,"stars":23,"repoUrl":24,"updatedAt":803},"building-react-quill-canvases","build React and Quill canvases","Author the React + Quill implementation of a PostHog canvas: the single-component contract, the allowed imports, Quill (PostHog's design system) component and composition rules, theme-aware design tokens, loading skeletons, and the in-canvas date picker. Use after building-canvases has routed a canvas request to a React implementation — dashboards, data boards, forms, tools, or any canvas that should look native to PostHog.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[794,795,798,800],{"name":711,"slug":712,"type":13},{"name":796,"slug":797,"type":13},"Frontend","frontend",{"name":799,"slug":38,"type":13},"React",{"name":801,"slug":802,"type":13},"UI Components","ui-components","2026-08-06T06:09:18.633724",{"slug":805,"name":805,"fn":806,"description":807,"org":808,"tags":809,"stars":23,"repoUrl":24,"updatedAt":818},"building-workflows","build and edit PostHog workflows","Build, edit, test, enable, and monitor PostHog workflows over MCP. Author the action\u002Fedge graph so it runs and opens cleanly in the visual editor, then change drafts surgically with patch operations. Use when asked to build, set up, automate, change, fix, or debug a workflow, campaign, broadcast, drip sequence, or event-triggered automation in the workflows product.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[810,811,814,815],{"name":708,"slug":709,"type":13},{"name":812,"slug":813,"type":13},"MCP","mcp",{"name":9,"slug":8,"type":13},{"name":816,"slug":817,"type":13},"Workflow Automation","workflow-automation","2026-08-06T05:36:26.504811",{"slug":820,"name":820,"fn":821,"description":822,"org":823,"tags":824,"stars":23,"repoUrl":24,"updatedAt":830},"check-posthog-loading","inspect PostHog SDK loading across URLs","Inspect how the PostHog JavaScript SDK is loaded across a list of URLs. Use to confirm consistent installation across pages, find pages missing the snippet, detect mismatched API keys or hosts between pages, and verify the load method (head snippet vs deferred vs array.js).\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[825,826,827,828,829],{"name":18,"slug":19,"type":13},{"name":680,"slug":681,"type":13},{"name":796,"slug":797,"type":13},{"name":629,"slug":630,"type":13},{"name":9,"slug":8,"type":13},"2026-05-07T05:56:19.828048",{"slug":832,"name":832,"fn":833,"description":834,"org":835,"tags":836,"stars":23,"repoUrl":24,"updatedAt":843},"consuming-endpoints-from-client-code","integrate PostHog endpoints into client applications","Wire a PostHog endpoint into a client app or SDK. Covers fetching the OpenAPI spec, generating a typed client with openapi-generator or @hey-api\u002Fopenapi-ts, sending the right auth header, shaping the variables payload (HogQL code_name vs insight breakdown property), handling rate-limit and materialised-endpoint error responses. Use when the user says \"how do I call my endpoint\", \"generate a client for this\", or \"what auth header do I use\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[837,840,841,842],{"name":838,"slug":839,"type":13},"API Development","api-development",{"name":796,"slug":797,"type":13},{"name":9,"slug":8,"type":13},{"name":21,"slug":22,"type":13},"2026-06-08T08:08:34.929454",243]