[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-posthog-signals-scout-revenue-analytics":3,"mdc-fvpxih-key":41,"related-repo-posthog-signals-scout-revenue-analytics":2116,"related-org-posthog-signals-scout-revenue-analytics":2234},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":26,"repoUrl":27,"updatedAt":28,"license":29,"forks":30,"topics":31,"repo":36,"sourceUrl":39,"mdContent":40},"signals-scout-revenue-analytics","monitor PostHog revenue analytics","Signals scout for PostHog revenue analytics. Watches for upstream failures (Stripe sync stalls, capture regressions), config drift, and goal-miss escalations, and files each validated finding as a report in the inbox.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"posthog","PostHog","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fposthog.png",[12,16,17,20,23],{"name":13,"slug":14,"type":15},"Observability","observability","tag",{"name":9,"slug":8,"type":15},{"name":18,"slug":19,"type":15},"Finance","finance",{"name":21,"slug":22,"type":15},"Analytics","analytics",{"name":24,"slug":25,"type":15},"Stripe","stripe",59,"https:\u002F\u002Fgithub.com\u002FPostHog\u002Fai-plugin","2026-07-18T05:11:25.450045",null,11,[32,33,34,35],"claude-code-plugin","codex-plugin","cursor-plugin","gemini-cli-extension",{"repoUrl":27,"stars":26,"forks":30,"topics":37,"description":38},[32,33,34,35],"Official PostHog plugin for Claude Code, Cursor, Gemini, Codex and other AI coding tools","https:\u002F\u002Fgithub.com\u002FPostHog\u002Fai-plugin\u002Ftree\u002FHEAD\u002Fskills\u002Fsignals-scout-revenue-analytics","---\nname: signals-scout-revenue-analytics\ndescription: >\n  Signals scout for PostHog revenue analytics. Watches for upstream failures (Stripe sync\n  stalls, capture regressions), config drift, and goal-miss escalations, and files each\n  validated finding as a report in the inbox.\ncompatibility: >\n  Designed for the PostHog Signals agent in a Claude sandbox with PostHog MCP scopes:\n  read-only analytics plus signal_scout_internal:write (for scratchpad) +\n  signal_scout_report:write (for emit-report\u002Fedit-report, granted because this scout authors\n  reports directly via the report channel). Assumes the signals-scout MCP tool family plus the\n  warehouse and analytics tools listed in the body's MCP tools section.\nallowed_tools:\n  - emit_report\n  - edit_report\nmetadata:\n  owner_team: signals\n  scope: revenue_analytics\n---\n\n# Signals scout: revenue analytics\n\nYou are a focused revenue analytics scout. Revenue analytics is a **derived product** — it doesn't have its own event stream; it standardizes data from two upstream paths into the `revenue_analytics_*` managed views (charge, customer, mrr, product, revenue_item, subscription):\n\n- **Events source** — team-configured revenue events (e.g. `purchase_completed`) with revenue \u002F currency \u002F subscription properties mapped via `RevenueAnalyticsConfig`.\n- **Data warehouse source** — Stripe (today) and other payment platforms, synced through the warehouse pipeline.\n\nBecause it's derived, your job is mostly **upstream watchdog**: when Stripe sync stalls or the revenue event stops firing, the dashboard silently shows wrong numbers and finance acts on stale data. That's the high-impact class. Movement in MRR \u002F churn \u002F ARR itself is secondary — the team is usually already watching that.\n\nRevenue numbers have a high panic radius — false positives erode trust faster here than in any other domain. When in doubt, write a scratchpad memory rather than a report.\n\nYou author reports directly via the report channel (`scout-emit-report` \u002F `scout-edit-report`): you've done the research, so you own each finding 1:1 end-to-end as an inbox report rather than firing a weak signal for a pipeline to cluster. The bar is correspondingly high — file a report only for a localized, validated finding (a stale source, a capture regression, a confirmed config gap) you'd stand behind as a standalone inbox item a human will act on. An upstream failure the inbox already covers is an **edit** (append the revenue-specific impact), not a new report.\n\n## Quick close-out: is revenue analytics even active?\n\nIf `external_data_sources` has no payment platform **and** no revenue event sits in `top_events`, revenue analytics isn't active on this project. Write one scratchpad entry:\n\n- key: `not-in-use:revenue_analytics:team{team_id}`\n- content: brief note (\"checked at {timestamp}, no payment platform, no revenue events\")\n\nClose out empty. Future revenue runs read this entry cold and short-circuit fast. Re-running with the same key idempotently refreshes the timestamp — the entry stays until revenue analytics actually becomes active, at which point the next run rewrites or deletes it.\n\n## How a run works\n\nCycle between these moves; skip what's not useful.\n\n### Get oriented\n\nThree cheap reads cold-start a run:\n\n- `scout-scratchpad-search` (`text=revenue` or `text=stripe`) — durable team steering. Entries with `pattern:`, `noise:`, `addressed:`, or `dedupe:` key prefixes, plus the team's known revenue event name, Stripe source label, currency mix, and goals.\n- `scout-runs-list` (last 7d) — what prior revenue runs found and ruled out.\n- `scout-project-profile-get` — `external_data_sources` (Stripe status), `top_events` (configured revenue event reach), `popular_insights` \u002F `recent_dashboards` (revenue chart load-bearingness), `product_intents` (stuck onboarding).\n\n### Profile shape — what's loud today?\n\n| Pattern                                                                                | What it usually means                                            |\n| -------------------------------------------------------------------------------------- | ---------------------------------------------------------------- |\n| Stripe-shaped `external_data_sources` row with `status = failed` or stuck `running`    | Revenue dashboard silently stale — high-impact upstream watchdog |\n| Configured revenue event missing or sharply down in `top_events`                       | Capture regression — MRR \u002F gross revenue dropping artificially   |\n| `popular_insights` includes revenue chart and chart's source is unhealthy              | Confirmed downstream impact — high-confidence finding            |\n| `product_intents` lists revenue analytics but no Stripe source and no event configured | Stuck onboarding — write memory, don't report                    |\n| Recent revenue dashboard view counts unchanged after a known revenue movement          | Team isn't watching — dashboard exists but isn't load-bearing    |\n\n### Explore\n\nPatterns to watch — starting points, not a checklist.\n\n#### Upstream sync stale, dashboard reads wrong\n\nStripe (or another payment platform) source is failed \u002F stuck \u002F cancelled. The dashboard at `\u002Frevenue` keeps rendering yesterday's MRR as today's. **Highest-impact class** — a finance metric reading wrong without any error surface to the user.\n\n1. `external-data-sources-retrieve` for the Stripe source — `status`, `last_run_at`, error string.\n2. `external-data-sync-logs` for the failure pattern — one-off vs recurring.\n3. `execute-sql` against `system.insights` filtered to `name ILIKE '%revenue%' OR query::text ILIKE '%revenue_analytics%'` for blast radius.\n4. Cross-check `inbox-reports-list` for an open warehouse-source report — if so, `append_note` the **revenue-specific** angle (which finance metrics are wrong) onto it rather than authoring a parallel report for the same warehouse failure.\n\nThe warehouse failure is the recovery action; the revenue angle is the **business impact** prose: which dashboards, who reads them, what's wrong by how much.\n\n#### Revenue event capture regression\n\nTeam configured `purchase_completed` (or similar) as their revenue event. Today it's missing from `top_events` or its 24h count is \u003C 30% of its prior baseline. MRR for event-source customers will be artificially low; the gross revenue chart will look like a step-change drop.\n\nCheap validation: `query-trends` on the event with a 14-day window — confirm the drop is real and isn't a weekend pattern. Pair with `read-data-schema event_properties` to check whether the revenue property itself stopped flowing (event still firing but with `null` revenue) — different upstream cause, same downstream symptom.\n\nHigh-confidence finding when:\n\n- 14-day trend shows a clear inflection, not a normal weekly cycle.\n- Event still defined in `RevenueAnalyticsConfig` (team didn't intentionally rename it).\n- Recent deploy \u002F SDK upgrade timing matches the inflection (hint, not proof).\n\n#### Subscription property missing → MRR is empty\n\nEvent source configured for a subscription business, but `RevenueAnalyticsConfig.events[].subscriptionProperty` is null. The MRR view will be empty because PostHog can't tell which charges belong to the same subscription. The dashboard renders but only gross revenue is meaningful.\n\nDetect: events configured with revenue + currency but no subscription property; gross-revenue chart populated, MRR chart empty. Scratchpad-level finding for new-onboarding teams; report-worthy if the team has been live long enough that they should have noticed.\n\n#### Currency mix surprise\n\n`execute-sql` on `revenue_analytics.all.revenue_analytics_charge`:\n\n```sql\nSELECT original_currency, count(), sum(original_amount)\nFROM revenue_analytics.all.revenue_analytics_charge\nWHERE timestamp > now() - INTERVAL 30 DAY\nGROUP BY 1 ORDER BY 2 DESC\n```\n\nA currency that's never appeared before, or whose share suddenly jumped, usually means either (a) the team is selling into a new market — write a scratchpad entry, no report, or (b) currency property is misconfigured and revenue is being mis-tagged. The (b) case shows up as a single dominant currency on a non-USD team or vice versa. Cross-reference with `RevenueAnalyticsEventItem.currencyProperty` to tell them apart.\n\n#### Stripe-customer ↔ PostHog-person join broken\n\nStripe customers should carry `posthog_person_distinct_id` metadata so PostHog can attach revenue to the person profile. If newly-created customers stop carrying that metadata (post-deploy regression in checkout flow), aggregate views still work but person-level revenue (group analytics, customer journeys) goes dark.\n\nDetect via the `customer` view: count of customers with non-null `posthog_person_distinct_id` in last 30d vs the 30d before. Scratchpad-worthy if the team isn't using person-level revenue features; report-worthy if they are (check `popular_insights` for person-breakdown revenue charts).\n\n#### Deferred revenue not deferring\n\nStripe source healthy, but invoice line items missing the `period` property. The dashboard will show monthly revenue lumpy (annual subscriptions land in one month) instead of spread across the service period. Check the `revenue_item` view: rows where `is_recurring = true` and `period_start` \u002F `period_end` are null. Report when more than ~20% of recurring rows are missing period info — finance reporting wrong in a subtle way.\n\n#### Goal miss without escalation\n\n`RevenueAnalyticsConfig.goals` carries `due_date` + `goal` + `mrr_or_gross`. If a goal's `due_date` is \u003C 14 days out and current MRR (or gross revenue) is trending under the goal, the team should already be reacting. If recent dashboard views haven't ticked up, they aren't watching. Surface the gap; let the team decide.\n\nDisqualifier: goals with `due_date` already past, where the team hasn't updated them — config debt, not active targets. Scratchpad entry, skip the report.\n\n#### Test-account contamination\n\n`RevenueAnalyticsConfig.filter_test_accounts = false` on a project with a `person.properties.email` filter set up for test accounts. Internal QA charges are being counted as real revenue. Easy scratchpad entry; report-worthy if the scratchpad shows the team has historically asked about \"revenue jumped overnight\" incidents and the cause was QA traffic.\n\n### Save memory as you go\n\nMemory is a continuous activity. Write a scratchpad entry whenever you observe something a future revenue run should know. Encode the \"category\" in the key prefix — `pattern:`, `noise:`, `addressed:`, `dedupe:`, plus `report:\u003Centity>` (the `report_id` of a report you authored, so the next run edits it) and `reviewer:\u003Carea>` (a resolved owner login) — so future runs find it with a single `text=` search:\n\n- key `pattern:revenue_analytics:event-config` — _\"Revenue event is `purchase_completed`; revenue prop is `revenue` (cents), currency prop is `currency`, subscription prop is `subscription_id`.\"_\n- key `pattern:revenue_analytics:stripe_prod` — _\"Stripe source `stripe_prod` is the team's primary; `stripe_test` is sandbox and its failures are expected.\"_\n- key `pattern:revenue_analytics:currency-mix` — _\"Reporting currency is USD; `original_currency` regularly includes EUR \u002F GBP \u002F CAD — multi-currency mix is normal for this team.\"_\n- key `pattern:revenue_analytics:q3-arr-goal` — _\"Team has revenue analytics goals configured; Q3 ARR target is $X by due_date 2026-09-30 — re-check progress monthly.\"_\n- key `pattern:revenue_analytics:dashboard-staleness` — _\"Revenue dashboard at `\u002Frevenue` was last viewed 2026-04-22; team isn't actively watching — report at a higher confidence threshold.\"_\n- key `addressed:revenue_analytics:test-accounts` — _\"`filter_test_accounts` is off; QA charges from `@example.com` accounts appear in revenue — already raised, team aware.\"_\n- key `report:revenue_analytics:stripe_prod` — _\"Authored report `0193…` for the stalled `stripe_prod` sync on 2026-06-30 (MRR + gross-revenue dashboards reading stale); edit it if the source is still failing next run.\"_\n- key `reviewer:revenue_analytics:billing` — _\"Billing \u002F revenue surface owner is `octocat` — route revenue-source reports here.\"_\n\nBy run #5 the scratchpad knows the team's revenue config, currency mix, which dashboards are load-bearing, and whether finance is actively watching — so when something regresses, the finding lands with the right context already attached.\n\n### Decide\n\nBefore you author, check whether this source \u002F metric already has a report — the `report:revenue_analytics:\u003Centity>` scratchpad pointer is the reliable path: it holds the `report_id`, so `inbox-reports-retrieve` it directly. With no pointer, fall back to an `inbox-reports-list` search (`ordering=-updated_at`) on the source label \u002F metric \u002F dashboard id. Then, for each candidate:\n\n- **Edit** the existing report via `scout-edit-report` when the inbox already covers the source or metric. A revenue issue is rarely brand-new — a Stripe source still failing, a revenue event still depressed: `append_note` with the fresh status and the revenue-specific impact (which metrics are wrong, by how much), or rewrite the title\u002Fsummary on a report you authored. This is the default when a match exists **and it's still live**; don't mint a near-duplicate. **Check the matched report's status first:** `edit-report` can't change status, so appending to a `resolved` \u002F `suppressed` \u002F `failed` report buries a real relapse — when the prior report is no longer live, author a fresh report and repoint `report:revenue_analytics:\u003Centity>` at the new id. If a warehouse-source failure report already exists (filed by the data-warehouse scout or the pipeline), `append_note` the revenue angle onto it rather than authoring a parallel report for the same upstream failure.\n- **Author** a fresh report via `scout-emit-report` when nothing live in the inbox covers it. A **strong finding** here: confidence ≥ 0.85, with concrete dashboard ids, source labels, view names, and quantified impact in the `evidence` (which finance metric is wrong, by how much, who reads it). A revenue finding is almost always an investigation, not a one-line code fix — the recovery action for a failing source lives in the warehouse, not a code PR — so set `actionability=requires_human_input` and leave `priority` \u002F `repository` unset. **Set `suggested_reviewers`** — resolve the owning person with `scout-members-list` (each member carries a resolved `github_login`; cache it under a `reviewer:revenue_analytics:\u003Carea>` key), or pass a `{user_uuid}` when your evidence already names the owner. It's how the report reaches a human; left empty it's assigned to nobody and likely missed. After authoring, write a `report:revenue_analytics:\u003Centity>` scratchpad entry with the `report_id` so the next run edits it instead of duplicating.\n- **Remember** via `scout-scratchpad-remember` if it's below the bar but worth carrying forward, or to record what you ruled out and why.\n- **Skip** with a one-line note if a scratchpad entry with a `noise:` \u002F `addressed:` \u002F `dedupe:` key prefix, or an existing inbox report, already covers it.\n\nThe harness prompt carries the full report-channel contract (field schema, safety × actionability status mapping, reviewer routing, the non-idempotency caveat, and the edit rules) — this section only adds the revenue-specific framing. Given revenue's high panic radius, keep the authoring bar high: fewer, better, well-routed reports.\n\n### Close out\n\n**Summarize the run** — one paragraph: looked at what, authored or edited which reports, remembered what, ruled out what. The harness writes that summary to the run row as searchable prose; future runs read it via `scout-runs-list`. Do **not** write a separate \"run metadata\" scratchpad entry — the run summary already serves that role.\n\n## Disqualifiers (skip these)\n\n- **Reporting currency just changed** — apparent step-change in all charts; not a regression. A `pattern:` scratchpad entry from a prior run usually flags this.\n- **Revenue analytics in beta on the team's plan** — some teams use it as preview-only. The scratchpad should record this; if no entry exists, write one and skip.\n- **Sandbox \u002F test Stripe source** — `prefix` like `test_` or `sandbox_` means the team is wiring up integration; failures here aren't production signal.\n- **Revenue event renamed by the team** — `RevenueAnalyticsConfig.events[].eventName` was updated recently; the \"missing event\" is the old name. Cross-check config recency before flagging.\n- **Goal expired with no follow-up** — config debt, not an active target. Scratchpad entry, skip.\n\nWhen in doubt, write a memory entry instead of authoring a report.\n\n## MCP tools\n\nDirect calls (read-only):\n\n- `external-data-sources-list` \u002F `external-data-sources-retrieve` — Stripe source health. Filter `source_type` to payment platforms.\n- `external-data-sync-logs` — failure history; one-off vs recurring upstream issues.\n- `read-data-schema events` \u002F `read-data-schema event_properties` — confirm revenue event + properties still flow.\n- `query-trends` — validate event-volume drops with a 14-day window and weekly comparison.\n- `execute-sql` against `revenue_analytics.all.revenue_analytics_\u003Ccharge|customer|mrr|revenue_item|subscription>` — managed views are the source of truth. Per-source views also exist: `\u003Csource>.\u003Cprefix>.revenue_analytics_\u003Cview_type>` (data warehouse) and `revenue_analytics.events.\u003Cevent_name>.revenue_analytics_\u003Cview_type>` (events).\n- `execute-sql` against `system.insights` \u002F `system.dashboards` — find revenue insights and dashboards that depend on a failing source (blast radius).\n- `dashboards-get-all` \u002F `dashboard-get` — the built-in revenue dashboard and any custom revenue dashboards.\n- `data-warehouse-data-health-issues-retrieve` — platform-detected issues on warehouse sources; revenue is one of the highest-priority downstream consumers.\n\nHarness-level:\n\n- `scout-project-profile-get` \u002F `scout-scratchpad-search` \u002F `scout-runs-list` \u002F `scout-runs-retrieve` — orientation + dedupe.\n- `inbox-reports-list` \u002F `inbox-reports-retrieve` — find an existing report before authoring.\n- `scout-emit-report` \u002F `scout-edit-report` — author a report \u002F edit an existing one (the report-channel contract is in the harness prompt).\n- `scout-members-list` — this project's members with their resolved `github_login`, for `suggested_reviewers` routing.\n- `scout-scratchpad-remember` — durable memory across runs.\n\nFor deeper investigation, the sandbox image bakes `posthog:auditing-warehouse-source-health` (catches Stripe-source failures upstream of revenue analytics) and `posthog:diagnosing-failed-warehouse-syncs` (recovery actions for a failing sync).\n\n## When to stop\n\n- No payment platform + no revenue event → close out empty (after writing the `not-in-use:` scratchpad entry).\n- Profile + scratchpad show a stable picture → close out empty.\n- A candidate matches a scratchpad entry with `noise:` \u002F `addressed:` \u002F `dedupe:` key prefix → skip.\n- You've validated some hypotheses and authored or edited what's solid → close out, even if there's more you could look at. Fewer, better reports — especially here, where panic radius is high.\n\n\"Looked but found nothing meaningful\" is a real outcome.\n",{"data":42,"body":50},{"name":4,"description":6,"compatibility":43,"allowed_tools":44,"metadata":47},"Designed for the PostHog Signals agent in a Claude sandbox with PostHog MCP scopes: read-only analytics plus signal_scout_internal:write (for scratchpad) + signal_scout_report:write (for emit-report\u002Fedit-report, granted because this scout authors reports directly via the report channel). Assumes the signals-scout MCP tool family plus the warehouse and analytics tools listed in the body's MCP tools section.\n",[45,46],"emit_report","edit_report",{"owner_team":48,"scope":49},"signals","revenue_analytics",{"type":51,"children":52},"root",[53,61,84,125,137,142,170,177,205,224,229,235,240,247,252,372,378,507,513,518,525,545,641,653,659,678,707,712,737,743,756,761,767,785,834,847,853,866,893,899,943,949,990,1002,1008,1027,1033,1095,1329,1334,1340,1383,1629,1634,1640,1664,1670,1759,1764,1770,1775,1925,1930,2028,2049,2055,2105,2110],{"type":54,"tag":55,"props":56,"children":57},"element","h1",{"id":4},[58],{"type":59,"value":60},"text","Signals scout: revenue analytics",{"type":54,"tag":62,"props":63,"children":64},"p",{},[65,67,73,75,82],{"type":59,"value":66},"You are a focused revenue analytics scout. Revenue analytics is a ",{"type":54,"tag":68,"props":69,"children":70},"strong",{},[71],{"type":59,"value":72},"derived product",{"type":59,"value":74}," — it doesn't have its own event stream; it standardizes data from two upstream paths into the ",{"type":54,"tag":76,"props":77,"children":79},"code",{"className":78},[],[80],{"type":59,"value":81},"revenue_analytics_*",{"type":59,"value":83}," managed views (charge, customer, mrr, product, revenue_item, subscription):",{"type":54,"tag":85,"props":86,"children":87},"ul",{},[88,115],{"type":54,"tag":89,"props":90,"children":91},"li",{},[92,97,99,105,107,113],{"type":54,"tag":68,"props":93,"children":94},{},[95],{"type":59,"value":96},"Events source",{"type":59,"value":98}," — team-configured revenue events (e.g. ",{"type":54,"tag":76,"props":100,"children":102},{"className":101},[],[103],{"type":59,"value":104},"purchase_completed",{"type":59,"value":106},") with revenue \u002F currency \u002F subscription properties mapped via ",{"type":54,"tag":76,"props":108,"children":110},{"className":109},[],[111],{"type":59,"value":112},"RevenueAnalyticsConfig",{"type":59,"value":114},".",{"type":54,"tag":89,"props":116,"children":117},{},[118,123],{"type":54,"tag":68,"props":119,"children":120},{},[121],{"type":59,"value":122},"Data warehouse source",{"type":59,"value":124}," — Stripe (today) and other payment platforms, synced through the warehouse pipeline.",{"type":54,"tag":62,"props":126,"children":127},{},[128,130,135],{"type":59,"value":129},"Because it's derived, your job is mostly ",{"type":54,"tag":68,"props":131,"children":132},{},[133],{"type":59,"value":134},"upstream watchdog",{"type":59,"value":136},": when Stripe sync stalls or the revenue event stops firing, the dashboard silently shows wrong numbers and finance acts on stale data. That's the high-impact class. Movement in MRR \u002F churn \u002F ARR itself is secondary — the team is usually already watching that.",{"type":54,"tag":62,"props":138,"children":139},{},[140],{"type":59,"value":141},"Revenue numbers have a high panic radius — false positives erode trust faster here than in any other domain. When in doubt, write a scratchpad memory rather than a report.",{"type":54,"tag":62,"props":143,"children":144},{},[145,147,153,155,161,163,168],{"type":59,"value":146},"You author reports directly via the report channel (",{"type":54,"tag":76,"props":148,"children":150},{"className":149},[],[151],{"type":59,"value":152},"scout-emit-report",{"type":59,"value":154}," \u002F ",{"type":54,"tag":76,"props":156,"children":158},{"className":157},[],[159],{"type":59,"value":160},"scout-edit-report",{"type":59,"value":162},"): you've done the research, so you own each finding 1:1 end-to-end as an inbox report rather than firing a weak signal for a pipeline to cluster. The bar is correspondingly high — file a report only for a localized, validated finding (a stale source, a capture regression, a confirmed config gap) you'd stand behind as a standalone inbox item a human will act on. 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Filter ",{"type":54,"tag":76,"props":1796,"children":1798},{"className":1797},[],[1799],{"type":59,"value":1800},"source_type",{"type":59,"value":1802}," to payment platforms.",{"type":54,"tag":89,"props":1804,"children":1805},{},[1806,1811],{"type":54,"tag":76,"props":1807,"children":1809},{"className":1808},[],[1810],{"type":59,"value":583},{"type":59,"value":1812}," — failure history; one-off vs recurring upstream issues.",{"type":54,"tag":89,"props":1814,"children":1815},{},[1816,1822,1823,1828],{"type":54,"tag":76,"props":1817,"children":1819},{"className":1818},[],[1820],{"type":59,"value":1821},"read-data-schema events",{"type":59,"value":154},{"type":54,"tag":76,"props":1824,"children":1826},{"className":1825},[],[1827],{"type":59,"value":696},{"type":59,"value":1829}," — confirm revenue event + properties still flow.",{"type":54,"tag":89,"props":1831,"children":1832},{},[1833,1838],{"type":54,"tag":76,"props":1834,"children":1836},{"className":1835},[],[1837],{"type":59,"value":688},{"type":59,"value":1839}," — validate event-volume drops with a 14-day window and weekly comparison.",{"type":54,"tag":89,"props":1841,"children":1842},{},[1843,1848,1849,1855,1857,1863,1865,1871],{"type":54,"tag":76,"props":1844,"children":1846},{"className":1845},[],[1847],{"type":59,"value":594},{"type":59,"value":596},{"type":54,"tag":76,"props":1850,"children":1852},{"className":1851},[],[1853],{"type":59,"value":1854},"revenue_analytics.all.revenue_analytics_\u003Ccharge|customer|mrr|revenue_item|subscription>",{"type":59,"value":1856}," — managed views are the source of truth. Per-source views also exist: ",{"type":54,"tag":76,"props":1858,"children":1860},{"className":1859},[],[1861],{"type":59,"value":1862},"\u003Csource>.\u003Cprefix>.revenue_analytics_\u003Cview_type>",{"type":59,"value":1864}," (data warehouse) and ",{"type":54,"tag":76,"props":1866,"children":1868},{"className":1867},[],[1869],{"type":59,"value":1870},"revenue_analytics.events.\u003Cevent_name>.revenue_analytics_\u003Cview_type>",{"type":59,"value":1872}," (events).",{"type":54,"tag":89,"props":1874,"children":1875},{},[1876,1881,1882,1887,1888,1894],{"type":54,"tag":76,"props":1877,"children":1879},{"className":1878},[],[1880],{"type":59,"value":594},{"type":59,"value":596},{"type":54,"tag":76,"props":1883,"children":1885},{"className":1884},[],[1886],{"type":59,"value":602},{"type":59,"value":154},{"type":54,"tag":76,"props":1889,"children":1891},{"className":1890},[],[1892],{"type":59,"value":1893},"system.dashboards",{"type":59,"value":1895}," — find revenue insights and dashboards that depend on a failing source (blast radius).",{"type":54,"tag":89,"props":1897,"children":1898},{},[1899,1905,1906,1912],{"type":54,"tag":76,"props":1900,"children":1902},{"className":1901},[],[1903],{"type":59,"value":1904},"dashboards-get-all",{"type":59,"value":154},{"type":54,"tag":76,"props":1907,"children":1909},{"className":1908},[],[1910],{"type":59,"value":1911},"dashboard-get",{"type":59,"value":1913}," — the built-in revenue dashboard and any custom revenue dashboards.",{"type":54,"tag":89,"props":1915,"children":1916},{},[1917,1923],{"type":54,"tag":76,"props":1918,"children":1920},{"className":1919},[],[1921],{"type":59,"value":1922},"data-warehouse-data-health-issues-retrieve",{"type":59,"value":1924}," — platform-detected issues on warehouse sources; revenue is one of the highest-priority downstream consumers.",{"type":54,"tag":62,"props":1926,"children":1927},{},[1928],{"type":59,"value":1929},"Harness-level:",{"type":54,"tag":85,"props":1931,"children":1932},{},[1933,1962,1978,1994,2018],{"type":54,"tag":89,"props":1934,"children":1935},{},[1936,1941,1942,1947,1948,1953,1954,1960],{"type":54,"tag":76,"props":1937,"children":1939},{"className":1938},[],[1940],{"type":59,"value":332},{"type":59,"value":154},{"type":54,"tag":76,"props":1943,"children":1945},{"className":1944},[],[1946],{"type":59,"value":263},{"type":59,"value":154},{"type":54,"tag":76,"props":1949,"children":1951},{"className":1950},[],[1952],{"type":59,"value":321},{"type":59,"value":154},{"type":54,"tag":76,"props":1955,"children":1957},{"className":1956},[],[1958],{"type":59,"value":1959},"scout-runs-retrieve",{"type":59,"value":1961}," — orientation + dedupe.",{"type":54,"tag":89,"props":1963,"children":1964},{},[1965,1970,1971,1976],{"type":54,"tag":76,"props":1966,"children":1968},{"className":1967},[],[1969],{"type":59,"value":623},{"type":59,"value":154},{"type":54,"tag":76,"props":1972,"children":1974},{"className":1973},[],[1975],{"type":59,"value":1365},{"type":59,"value":1977}," — find an existing report before authoring.",{"type":54,"tag":89,"props":1979,"children":1980},{},[1981,1986,1987,1992],{"type":54,"tag":76,"props":1982,"children":1984},{"className":1983},[],[1985],{"type":59,"value":152},{"type":59,"value":154},{"type":54,"tag":76,"props":1988,"children":1990},{"className":1989},[],[1991],{"type":59,"value":160},{"type":59,"value":1993}," — author a report \u002F edit an existing one (the report-channel contract is in the harness prompt).",{"type":54,"tag":89,"props":1995,"children":1996},{},[1997,2002,2004,2009,2011,2016],{"type":54,"tag":76,"props":1998,"children":2000},{"className":1999},[],[2001],{"type":59,"value":1541},{"type":59,"value":2003}," — this project's members with their resolved ",{"type":54,"tag":76,"props":2005,"children":2007},{"className":2006},[],[2008],{"type":59,"value":1549},{"type":59,"value":2010},", for ",{"type":54,"tag":76,"props":2012,"children":2014},{"className":2013},[],[2015],{"type":59,"value":1533},{"type":59,"value":2017}," routing.",{"type":54,"tag":89,"props":2019,"children":2020},{},[2021,2026],{"type":54,"tag":76,"props":2022,"children":2024},{"className":2023},[],[2025],{"type":59,"value":1597},{"type":59,"value":2027}," — durable memory across runs.",{"type":54,"tag":62,"props":2029,"children":2030},{},[2031,2033,2039,2041,2047],{"type":59,"value":2032},"For deeper investigation, the sandbox image bakes ",{"type":54,"tag":76,"props":2034,"children":2036},{"className":2035},[],[2037],{"type":59,"value":2038},"posthog:auditing-warehouse-source-health",{"type":59,"value":2040}," (catches Stripe-source failures upstream of revenue analytics) and ",{"type":54,"tag":76,"props":2042,"children":2044},{"className":2043},[],[2045],{"type":59,"value":2046},"posthog:diagnosing-failed-warehouse-syncs",{"type":59,"value":2048}," (recovery actions for a failing sync).",{"type":54,"tag":171,"props":2050,"children":2052},{"id":2051},"when-to-stop",[2053],{"type":59,"value":2054},"When to stop",{"type":54,"tag":85,"props":2056,"children":2057},{},[2058,2071,2076,2100],{"type":54,"tag":89,"props":2059,"children":2060},{},[2061,2063,2069],{"type":59,"value":2062},"No payment platform + no revenue event → close out empty (after writing the ",{"type":54,"tag":76,"props":2064,"children":2066},{"className":2065},[],[2067],{"type":59,"value":2068},"not-in-use:",{"type":59,"value":2070}," scratchpad entry).",{"type":54,"tag":89,"props":2072,"children":2073},{},[2074],{"type":59,"value":2075},"Profile + scratchpad show a stable picture → close out empty.",{"type":54,"tag":89,"props":2077,"children":2078},{},[2079,2081,2086,2087,2092,2093,2098],{"type":59,"value":2080},"A candidate matches a scratchpad entry with ",{"type":54,"tag":76,"props":2082,"children":2084},{"className":2083},[],[2085],{"type":59,"value":295},{"type":59,"value":154},{"type":54,"tag":76,"props":2088,"children":2090},{"className":2089},[],[2091],{"type":59,"value":302},{"type":59,"value":154},{"type":54,"tag":76,"props":2094,"children":2096},{"className":2095},[],[2097],{"type":59,"value":310},{"type":59,"value":2099}," key prefix → skip.",{"type":54,"tag":89,"props":2101,"children":2102},{},[2103],{"type":59,"value":2104},"You've validated some hypotheses and authored or edited what's solid → close out, even if there's more you could look at. Fewer, better reports — especially here, where panic radius is high.",{"type":54,"tag":62,"props":2106,"children":2107},{},[2108],{"type":59,"value":2109},"\"Looked but found nothing meaningful\" is a real outcome.",{"type":54,"tag":2111,"props":2112,"children":2113},"style",{},[2114],{"type":59,"value":2115},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":2117,"total":2233},[2118,2133,2151,2168,2183,2197,2215],{"slug":2119,"name":2119,"fn":2120,"description":2121,"org":2122,"tags":2123,"stars":26,"repoUrl":27,"updatedAt":2132},"analyzing-experiment-session-replays","analyze session replays for PostHog experiments","Analyze session replay patterns across experiment variants to understand user behavior differences. Use when the user wants to see how users interact with different experiment variants, identify usability issues, compare behavior patterns between control and test groups, or get qualitative insights to complement quantitative experiment results.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2124,2125,2128,2129],{"name":21,"slug":22,"type":15},{"name":2126,"slug":2127,"type":15},"Design","design",{"name":9,"slug":8,"type":15},{"name":2130,"slug":2131,"type":15},"User Research","user-research","2026-04-06T18:44:38.291781",{"slug":2134,"name":2134,"fn":2135,"description":2136,"org":2137,"tags":2138,"stars":26,"repoUrl":27,"updatedAt":2150},"assessing-heatmaps","analyze page heatmaps and suggest improvements","Assesses what a page's heatmap is telling you and recommends concrete changes. Pulls click \u002F rageclick \u002F scroll-depth data for a URL, names the hot elements by cross-referencing autocapture events on the same page, and can create a saved heatmap the user opens in PostHog, then summarizes the behavior and proposes improvements.\nTRIGGER when: user asks what a heatmap shows, why people aren't clicking something, where users rage-click, how far they scroll, what to change on a page based on heatmap\u002Fclick data, or to 'analyze\u002Fassess\u002Freview the heatmap' for a URL.\nDO NOT TRIGGER when: the user only wants to create a saved heatmap screenshot with no analysis (use heatmaps-saved-create directly), or is asking about session replay in general (use investigating-replay).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2139,2140,2143,2144,2147],{"name":21,"slug":22,"type":15},{"name":2141,"slug":2142,"type":15},"Frontend","frontend",{"name":9,"slug":8,"type":15},{"name":2145,"slug":2146,"type":15},"Product Management","product-management",{"name":2148,"slug":2149,"type":15},"UX Design","ux-design","2026-06-05T07:40:43.37798",{"slug":2152,"name":2152,"fn":2153,"description":2154,"org":2155,"tags":2156,"stars":26,"repoUrl":27,"updatedAt":2167},"auditing-experiments-flags","audit PostHog experiments and feature flags","Audit PostHog experiments and feature flags for configuration issues, staleness, and best-practice violations. Read when the user asks to audit, health-check, or review experiments or feature flags, check flag hygiene, or verify experiment setup.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2157,2160,2163,2164],{"name":2158,"slug":2159,"type":15},"Audit","audit",{"name":2161,"slug":2162,"type":15},"Feature Flags","feature-flags",{"name":9,"slug":8,"type":15},{"name":2165,"slug":2166,"type":15},"QA","qa","2026-04-06T18:44:30.657553",{"slug":2169,"name":2169,"fn":2170,"description":2171,"org":2172,"tags":2173,"stars":26,"repoUrl":27,"updatedAt":2182},"authoring-scouts","author and edit PostHog Signals scouts","How to author, edit, and adapt PostHog Signals scouts — the scheduled agents that scan a project and write reports into the Signals inbox. Use when a user wants to customize a canonical scout for their own setup (narrow its scope, retune its thresholds, add disqualifiers), tweak a scout's schedule or dry-run posture, or write a brand-new scout from scratch for a specific use case (a custom event, a product surface no canonical scout covers), or steer a scout without editing it at all by leaving it a note. Covers the scout SKILL.md anatomy, the report contract, the dedupe + scratchpad-memory conventions, the scout-notes steering channel, the per-team skills-store path vs the canonical in-repo path, and the write-and-inspect test loop (with dry-run as an optional safety net). Trigger on \"write\u002Fedit\u002Fcustomize a signals scout\", \"new scout for X\", \"tune my scout schedule\", \"make a scout that watches \u003Cevent>\", \"leave a note for \u002F give feedback to a scout\", \"tell the scouts about X\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2174,2177,2180,2181],{"name":2175,"slug":2176,"type":15},"Agents","agents",{"name":2178,"slug":2179,"type":15},"Automation","automation",{"name":13,"slug":14,"type":15},{"name":9,"slug":8,"type":15},"2026-07-28T05:33:45.509154",{"slug":2184,"name":2184,"fn":2185,"description":2186,"org":2187,"tags":2188,"stars":26,"repoUrl":27,"updatedAt":2196},"building-a-dashboard","build and update PostHog dashboards","Build a new dashboard, or update an existing one, from a set of insights — the same job the in-app assistant does with its upsert-dashboard tool, but over MCP. Use when a user asks to create a dashboard, put several metrics\u002Fcharts together on one page, assemble a dashboard for a topic (product analytics, retention, revenue, activation, etc.), or add\u002Fremove\u002Freplace insights on a dashboard they already have. Covers deciding create vs update, reusing existing insights vs creating new ones, and using PostHog's vetted dashboard templates as reference for what a strong dashboard on a topic looks like.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2189,2190,2193],{"name":21,"slug":22,"type":15},{"name":2191,"slug":2192,"type":15},"Dashboards","dashboards",{"name":2194,"slug":2195,"type":15},"MCP","mcp","2026-07-21T06:07:38.060598",{"slug":2198,"name":2198,"fn":2199,"description":2200,"org":2201,"tags":2202,"stars":26,"repoUrl":27,"updatedAt":2214},"checking-deploy-timing","correlate PostHog deployments with GitHub commits","Determine when a PostHog code change reached a given environment by reading the hidden GIT deploy annotations in the project and correlating them with the merge commit on GitHub. Use when PostHog staff ask \"when was X deployed\", \"is my change live in the US\u002FEU yet\", \"has my PR shipped\", \"did the fix roll out to prod-us\", or otherwise want to know whether\u002Fwhen a commit, PR, or feature went out to a region. Do not answer deploy-timing questions from event\u002Fdata volume alone — that only shows when data changed, not when code shipped.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2203,2206,2209,2212,2213],{"name":2204,"slug":2205,"type":15},"Deployment","deployment",{"name":2207,"slug":2208,"type":15},"Git","git",{"name":2210,"slug":2211,"type":15},"GitHub","github",{"name":13,"slug":14,"type":15},{"name":9,"slug":8,"type":15},"2026-06-28T07:46:59.53536",{"slug":2216,"name":2216,"fn":2217,"description":2218,"org":2219,"tags":2220,"stars":26,"repoUrl":27,"updatedAt":2232},"choosing-trend-or-slope-view","visualize trends and growth over time","Clarify how to visualize change over a time range before building a trend. Use whenever the user asks how much something changed, grew, dropped, improved, or regressed between two points or periods — \"how much did X change from A to B\", \"before vs after\", \"start vs end\", \"week over week\", \"compare this month to last\", \"change over time\" — or mentions a \"slope chart\" \u002F \"slopegraph\". Two readings of \"change\" need different charts: the whole trend (a line, every interval) versus just the two endpoints (a slope, start vs end). Ask which they want, then render it. Not for choosing a saved insight ChartDisplayType in the insight editor.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2221,2222,2225,2228,2229],{"name":21,"slug":22,"type":15},{"name":2223,"slug":2224,"type":15},"Charts","charts",{"name":2226,"slug":2227,"type":15},"Data Visualization","data-visualization",{"name":9,"slug":8,"type":15},{"name":2230,"slug":2231,"type":15},"Reporting","reporting","2026-06-18T08:18:57.960157",56,{"items":2235,"total":2394},[2236,2251,2261,2274,2287,2302,2318,2331,2343,2358,2368,2384],{"slug":2237,"name":2237,"fn":2238,"description":2239,"org":2240,"tags":2241,"stars":2248,"repoUrl":2249,"updatedAt":2250},"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},[2242,2243,2246,2247],{"name":21,"slug":22,"type":15},{"name":2244,"slug":2245,"type":15},"Cost Optimization","cost-optimization",{"name":13,"slug":14,"type":15},{"name":9,"slug":8,"type":15},35568,"https:\u002F\u002Fgithub.com\u002FPostHog\u002Fposthog","2026-07-28T05:34:11.117757",{"slug":2252,"name":2252,"fn":2253,"description":2254,"org":2255,"tags":2256,"stars":2248,"repoUrl":2249,"updatedAt":2260},"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},[2257,2258,2259],{"name":21,"slug":22,"type":15},{"name":2158,"slug":2159,"type":15},{"name":9,"slug":8,"type":15},"2026-06-08T08:08:33.693989",{"slug":2262,"name":2262,"fn":2263,"description":2264,"org":2265,"tags":2266,"stars":2248,"repoUrl":2249,"updatedAt":2273},"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},[2267,2268,2271,2272],{"name":2158,"slug":2159,"type":15},{"name":2269,"slug":2270,"type":15},"Data Warehouse","data-warehouse",{"name":13,"slug":14,"type":15},{"name":9,"slug":8,"type":15},"2026-06-18T08:22:57.67984",{"slug":2275,"name":2275,"fn":2276,"description":2277,"org":2278,"tags":2279,"stars":2248,"repoUrl":2249,"updatedAt":2286},"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},[2280,2281,2282,2285],{"name":2158,"slug":2159,"type":15},{"name":2269,"slug":2270,"type":15},{"name":2283,"slug":2284,"type":15},"Performance","performance",{"name":9,"slug":8,"type":15},"2026-06-18T08:25:10.936787",{"slug":2288,"name":2288,"fn":2289,"description":2290,"org":2291,"tags":2292,"stars":2248,"repoUrl":2249,"updatedAt":2301},"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},[2293,2296,2299,2300],{"name":2294,"slug":2295,"type":15},"Alerting","alerting",{"name":2297,"slug":2298,"type":15},"Debugging","debugging",{"name":13,"slug":14,"type":15},{"name":9,"slug":8,"type":15},"2026-06-18T08:24:40.318583",{"slug":2303,"name":2303,"fn":2304,"description":2305,"org":2306,"tags":2307,"stars":2248,"repoUrl":2249,"updatedAt":2317},"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},[2308,2309,2312,2313,2316],{"name":21,"slug":22,"type":15},{"name":2310,"slug":2311,"type":15},"Monitoring","monitoring",{"name":13,"slug":14,"type":15},{"name":2314,"slug":2315,"type":15},"Operations","operations",{"name":9,"slug":8,"type":15},"2026-07-18T05:10:54.430898",{"slug":2319,"name":2319,"fn":2320,"description":2321,"org":2322,"tags":2323,"stars":2248,"repoUrl":2249,"updatedAt":2330},"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},[2324,2325,2326,2327],{"name":2178,"slug":2179,"type":15},{"name":2194,"slug":2195,"type":15},{"name":9,"slug":8,"type":15},{"name":2328,"slug":2329,"type":15},"Workflow Automation","workflow-automation","2026-07-28T05:34:12.167015",{"slug":2332,"name":2332,"fn":2333,"description":2334,"org":2335,"tags":2336,"stars":2248,"repoUrl":2249,"updatedAt":2342},"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},[2337,2338,2339,2340,2341],{"name":21,"slug":22,"type":15},{"name":2297,"slug":2298,"type":15},{"name":2141,"slug":2142,"type":15},{"name":13,"slug":14,"type":15},{"name":9,"slug":8,"type":15},"2026-05-07T05:56:19.828048",{"slug":2344,"name":2344,"fn":2345,"description":2346,"org":2347,"tags":2348,"stars":2248,"repoUrl":2249,"updatedAt":2357},"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},[2349,2352,2353,2354],{"name":2350,"slug":2351,"type":15},"API Development","api-development",{"name":2141,"slug":2142,"type":15},{"name":9,"slug":8,"type":15},{"name":2355,"slug":2356,"type":15},"SDK","sdk","2026-06-08T08:08:34.929454",{"slug":2359,"name":2359,"fn":2360,"description":2361,"org":2362,"tags":2363,"stars":2248,"repoUrl":2249,"updatedAt":2367},"copying-endpoints-across-projects","copy PostHog endpoints across projects","Copy a PostHog endpoint (a saved HogQL\u002Finsight query exposed as an API route) to another project in the same organization, or duplicate it under a new name in the same project. Use when the user wants to duplicate an endpoint, promote an endpoint from staging to production, replicate an endpoint's query\u002Fvariables\u002Ffreshness config in another workspace, or clone an endpoint to iterate on it. Unlike feature flags and experiments, endpoints have NO native cross-project copy tool — this skill covers the read-then-recreate flow (endpoint-get then endpoint-create), the active-project switching it requires, name-collision checks, and the safe defaults (land unmaterialised in the target, verify with endpoint-run). Does not cover editing endpoint versions (see managing-endpoint-versions) or authoring a brand-new endpoint from scratch (see creating-an-endpoint).\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2364,2365,2366],{"name":2350,"slug":2351,"type":15},{"name":2314,"slug":2315,"type":15},{"name":9,"slug":8,"type":15},"2026-07-15T05:29:58.442727",{"slug":2369,"name":2369,"fn":2370,"description":2371,"org":2372,"tags":2373,"stars":2248,"repoUrl":2249,"updatedAt":2383},"creating-ai-subscription","schedule recurring AI-generated PostHog reports","Create a recurring AI-generated PostHog report — schedule a free-text prompt to run on a cron, with the LLM-synthesized markdown delivered to email or Slack on each tick. Use when the user wants a recurring AI summary of X on any cadence (daily, weekly, monthly, yearly) rather than a one-off report. (To attach an AI summary to an existing insight\u002Fdashboard subscription instead of a free-text prompt, see `managing-subscriptions` and its `summary_enabled` option.)\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2374,2375,2378,2379,2380],{"name":2178,"slug":2179,"type":15},{"name":2376,"slug":2377,"type":15},"Email","email",{"name":9,"slug":8,"type":15},{"name":2230,"slug":2231,"type":15},{"name":2381,"slug":2382,"type":15},"Slack","slack","2026-06-09T07:32:27.935712",{"slug":2385,"name":2385,"fn":2386,"description":2387,"org":2388,"tags":2389,"stars":2248,"repoUrl":2249,"updatedAt":2393},"creating-an-endpoint","create PostHog API endpoints","Create a PostHog endpoint with the right shape on the first try — covers query kind choice, name conventions, what to expose as variables (HogQL code_name vs insight breakdown), data_freshness_seconds, and whether to materialise on day one. Use when the user says \"create an endpoint\", \"expose this query as an API\", \"turn this insight into an endpoint\", or asks for help structuring a new endpoint. Steers away from common mistakes: materialising a query with cohort breakdowns or compare mode, inline-only variables on a materialised endpoint, unbounded date ranges, ambiguous names.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2390,2391,2392],{"name":21,"slug":22,"type":15},{"name":2350,"slug":2351,"type":15},{"name":9,"slug":8,"type":15},"2026-06-08T08:08:29.624498",231]