Agent Native

signals-scout-revenue-analytics

This skill monitors PostHog's revenue analytics for upstream failures and configuration issues.

by PostHogOfficial publisherNot reviewed

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Agents
Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode
License
MIT (permissive)
Pin
244c70dpinned Oct 9, 2026
Context cost
about 5,600 tokenswhen the skill loads
GitHub stars
40,191on posthog/posthog
Scripts
None found

What it does

“Signals scout for PostHog revenue analytics. Watches for upstream failures (Stripe sync stalls, capture regressions), and config drift.”
The author's description, from SKILL.md

Generated summary from the skill's own text

This skill monitors PostHog's revenue analytics for upstream failures and configuration issues. It watches for Stripe sync stalls, capture regressions in revenue events, and config drift that cause revenue dashboards to display stale or incorrect data. The skill reads revenue configuration, profiles data health, and authors reports with high confidence when it finds localized, validated issues like failed payment platform syncs or missing subscription properties.

When to use it

  • Stripe or payment platform sync is stuck or failed and revenue dashboards show stale metrics
  • Revenue event configured in PostHog stops firing or drops sharply in event volume
  • Revenue event missing subscription property so MRR calculations are empty or broken
  • Currency in charges suddenly changes or mixes unexpectedly across sources

When not to

  • Reporting currency was intentionally changed by the team
  • Revenue analytics feature is in beta preview mode only
  • Testing or sandbox Stripe source with expected integration failures

Install

These commands install from the publisher's repository and need no account.

skills CLI

npx skills add posthog/posthog --skill signals-scout-revenue-analytics

Installs from the repository's default branch, which may have changed since the commit we checked.

GitHub CLI 2.90 or later

gh skill install posthog/posthog signals-scout-revenue-analytics@244c70d066c0b441e3b8cc6875f914c5e09c42b3

Installs the commit we checked (244c70d).

Copy by hand

Download the folder at 244c70d and put it in .claude/skills/signals-scout-revenue-analytics for Claude Code and in .agents/skills/signals-scout-revenue-analytics for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode.

Skill folder on GitHub at 244c70d

Claude Code plugin

/plugin install posthog@claude-plugins-official

The publisher's plugin in Claude's official marketplace. It may hold more than this skill, and we have not pinned it.

Copy for your agent

A prompt for any coding agent. It installs this skill from GitHub at the pinned commit, copies the files as they are, and runs nothing unless you ask.

Prompt

Install the agent skill "signals-scout-revenue-analytics" by PostHog.

Source, pinned to commit 244c70d066c0b441e3b8cc6875f914c5e09c42b3:
https://github.com/posthog/posthog/tree/244c70d066c0b441e3b8cc6875f914c5e09c42b3/products/signals/skills/signals-scout-revenue-analytics

1. Download that folder at exactly this commit. Do not use the default branch.
2. Copy every file unchanged, keeping the folder structure, into .claude/skills/signals-scout-revenue-analytics/ for Claude Code and .agents/skills/signals-scout-revenue-analytics/ for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode. Create the folders if they do not exist.
3. Do not edit the files, and do not run any script in the folder unless I ask you to.
4. When you are done, list the files you copied and where you put them.

Listing and checks: https://www.agentnative.dev/skills/posthog/signals-scout-revenue-analytics-posthog

SKILL.md at the pin

---
name: signals-scout-revenue-analytics
scout-display-name: Revenue analytics
description: >
  Signals scout for PostHog revenue analytics. Watches for upstream failures (Stripe sync
  stalls, capture regressions), and config drift.
compatibility: >
  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/edit-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.
allowed_tools:
  - emit_report
  - edit_report
metadata:
  owner_team: signals
  scope: revenue_analytics
---

# Signals scout: revenue analytics

You 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):

- **Events source** — team-configured revenue events (e.g. `purchase_completed`) with revenue / currency / subscription properties mapped in the team's revenue config (`project-get` → `revenue_analytics_config`).
- **Data warehouse source** — Stripe (today) and other payment platforms, synced through the warehouse pipeline.

Because 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 / churn / ARR itself is secondary — the team is usually already watching that.

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.

You author reports directly via the report channel (`scout-emit-report` / `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.

## Read the revenue config

`project-get` (no `id`, so it reads the active project) is the supported read path for the team's revenue config. Its `revenue_analytics_config` field carries:

- `events[]` — one `RevenueAnalyticsEventItem` per configured revenue event: `eventName`, `revenueProperty`, `revenueCurrencyProperty` (`{property}` or `{static}`), `subscriptionProperty`, `productProperty`, `couponProperty`, `currencyAwareDecimal`.
- `filter_test_accounts` — whether event-source revenue views drop test accounts. Stripe and other warehouse views ignore it.

Revenue goals no longer exist. Do not look for `goals`.

If `project-get` fails, fall back to the managed views. There is no cross-source view. Each configured event builds its own views named `revenue_analytics.events.<event_name>.<kind>_events_revenue_view`, where every non-alphanumeric character in the event name becomes `_`. List the event charge views:

```sql
SELECT table_name
FROM system.information_schema.tables
WHERE table_name LIKE 'revenue_analytics.events.%.charge_events_revenue_view'
```

To check the volume of one event, query its view:

```sql
SELECT event_name, count() AS charges, max(timestamp) AS last_charge
FROM revenue_analytics.events.<event_name>.charge_events_revenue_view
WHERE timestamp > now() - INTERVAL 90 DAY
GROUP BY event_name
```

The fallback has limits. Say so in any finding that relies on it:

- A view name carries the event name with `_` in place of special characters. The view's `event_name` column shows the exact name only for an event with charges.
- It does not show the property mapping. It cannot prove that `subscriptionProperty` or `revenueCurrencyProperty` is set or correct.
- It does not show `filter_test_accounts`.

## Quick close-out: is revenue analytics even active?

Revenue analytics is active when either source is present:

- `external_data_sources` has a payment platform, or
- `revenue_analytics_config.events` from `project-get` is not empty.

`top_events` does not prove that revenue analytics is inactive. A low-volume revenue event often falls out of `top_events`. Use `top_events` only to check the reach of an event that the config names.

If neither source is present, write one scratchpad entry:

- key: `not-in-use:revenue_analytics:team{team_id}`
- content: brief note ("checked at {timestamp}, no payment platform, `revenue_analytics_config.events` empty")

Close 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.

If `project-get` failed and the fallback listing failed or found no event charge views, do not write the `not-in-use:` entry. The fallback cannot prove that no event is configured. If `external_data_sources` has a payment platform, continue the run and check that source. Otherwise, close out empty. In both cases, say in the run summary that the config was unreadable.

## How a run works

Cycle between these moves; skip what's not useful.

### Get oriented

Four cheap reads cold-start a run:

- `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, and currency mix.
- `scout-runs-list` (last 7d) — what prior revenue runs found and ruled out.
- `project-get` — `revenue_analytics_config` (configured revenue events and their property mapping, `filter_test_accounts`). See [Read the revenue config](#read-the-revenue-config).
- `scout-project-profile-get` — `external_data_sources` (Stripe status), `top_events` (reach of the events that the config names), `popular_insights` / `recent_dashboards` (revenue chart load-bearingness), `product_intents` (stuck onboarding).

### Profile shape — what's loud today?

| Pattern                                                                                                       | What it usually means                                            |
| ------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------- |
| Stripe-shaped `external_data_sources` row with `status = failed` or stuck `running`                           | Revenue dashboard silently stale — high-impact upstream watchdog |
| Configured revenue event missing or sharply down in `top_events`                                              | Capture regression — MRR / gross revenue dropping artificially   |
| `popular_insights` includes revenue chart and chart's source is unhealthy                                     | Confirmed downstream impact — high-confidence finding            |
| `product_intents` lists revenue analytics but no Stripe source and `revenue_analytics_config.events` is empty | Stuck onboarding — write memory, don't report                    |
| Recent revenue dashboard view counts unchanged after a known revenue movement                                 | Team isn't watching — dashboard exists but isn't load-bearing    |

### Explore

Patterns to watch — starting points, not a checklist.

#### Upstream sync stale, dashboard reads wrong

Stripe (or another payment platform) source is failed / stuck / cancelled. The dashboard at `/revenue` keeps rendering yesterday's MRR as today's. **Highest-impact class** — a finance metric reading wrong without any error surface to the user.

1. `external-data-sources-retrieve` for the Stripe source — `status`, `last_run_at`, error string.
2. `external-data-sync-logs` for the failure pattern — one-off vs recurring.
3. `execute-sql` against `system.insights` filtered to `name ILIKE '%revenue%' OR query::text ILIKE '%revenue_analytics%'` for blast radius.
4. 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.

The 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.

#### Revenue event capture regression

Team configured `purchase_completed` (or similar) as their revenue event. Today it's missing from `top_events` or its 24h count is < 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.

Cheap 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.

High-confidence finding when:

- 14-day trend shows a clear inflection, not a normal weekly cycle.
- Event still in `revenue_analytics_config.events[].eventName` from `project-get` (team didn't intentionally rename it).
- Recent deploy / SDK upgrade timing matches the inflection (hint, not proof).

#### Subscription property missing → MRR is empty

Event source configured for a subscription business, but `revenue_analytics_config.events[].subscriptionProperty` from `project-get` 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.

Detect: events configured with revenue + currency but no subscription property; gross-revenue chart populated, MRR chart empty. The managed-view fallback cannot show the property mapping, so do not report this finding without `project-get`. Scratchpad-level finding for new-onboarding teams; report-worthy if the team has been live long enough that they should have noticed.

#### Currency mix surprise

There is no cross-source charge view. List the charge view of every source:

```sql
SELECT table_name
FROM system.information_schema.tables
WHERE table_name LIKE '%.charge_revenue_view' OR table_name LIKE '%.charge_events_revenue_view'
```

Then run `execute-sql` on each charge view:

```sql
SELECT source_label, original_currency, count(), sum(original_amount)
FROM <charge_view>
WHERE timestamp > now() - INTERVAL 30 DAY
GROUP BY 1, 2 ORDER BY 3 DESC
```

A 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. Read each `source_label` on its own, because `revenueCurrencyProperty` controls only event charges. For a `revenue_analytics.events.<event>` label, cross-reference that event's `revenue_analytics_config.events[].revenueCurrencyProperty` from `project-get` to tell them apart: `{static: "USD"}` tags every charge of that event with one currency, and `{property: ...}` reads it from the event. A warehouse label (e.g. `stripe.<prefix>`) takes its currency from the source's own data, so do not blame the event config for a shift there.

#### Stripe-customer ↔ PostHog-person join broken

Stripe 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.

Detect 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).

#### Deferred revenue not deferring

Stripe 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` / `period_end` are null. Report when more than ~20% of recurring rows are missing period info — finance reporting wrong in a subtle way.

#### Test-account contamination

`revenue_analytics_config.filter_test_accounts = false` (from `project-get`) on a project with configured revenue events and a `person.properties.email` filter set up for test accounts. Internal QA charges from those events are being counted as real revenue. The flag controls only event-source views, so it does not explain QA charges in a Stripe or other warehouse view, and turning it on does not remove them. 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.

### Save memory as you go

Memory 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:<entity>` (the `report_id` of a report you authored, so the next run edits it) and `reviewer:<area>` (a resolved owner login) — so future runs find it with a single `text=` search:

- 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`."_
- key `pattern:revenue_analytics:stripe_prod` — _"Stripe source `stripe_prod` is the team's primary; `stripe_test` is sandbox and its failures are expected."_
- key `pattern:revenue_analytics:currency-mix` — _"Reporting currency is USD; `original_currency` regularly includes EUR / GBP / CAD — multi-currency mix is normal for this team."_
- key `pattern:revenue_analytics:dashboard-staleness` — _"Revenue dashboard at `/revenue` was last viewed 2026-04-22; team isn't actively watching — report at a higher confidence threshold."_
- key `addressed:revenue_analytics:test-accounts` — _"`filter_test_accounts` is off; QA charges from `@example.com` accounts appear in revenue — already raised, team aware."_
- 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."_
- key `reviewer:revenue_analytics:billing` — _"Billing / revenue surface owner is `octocat` — route revenue-source reports here."_

By 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.

### Decide

Before you author, check whether this source / metric already has a report — the `report:revenue_analytics:<entity>` 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 / metric / dashboard id. Then, for each candidate:

- **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: use `append_evidence` for the fresh status and the revenue-specific impact (which metrics are wrong, by how much), or rewrite the title/summary 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` / `suppressed` / `failed` report buries a real relapse — when the prior report is no longer live, author a fresh report and repoint `report:revenue_analytics:<entity>` 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.
- **Author** a fresh report via `scout-emit-report` when nothing live in the inbox covers it. A **strong finding** here: the evidence settles it without a hedge, 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). When the finding is a metric move — an MRR step, a revenue cliff — rather than a config gap, attach the affected series via `charts` so the step and its onset are visible. 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` / `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:<area>` 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:<entity>` scratchpad entry with the `report_id` so the next run edits it instead of duplicating.
- **Remember** via `scout-scratchpad-remember` if it's below the bar but worth carrying forward, or to record what you ruled out and why.
- **Skip** with a one-line note if a scratchpad entry with a `noise:` / `addressed:` / `dedupe:` key prefix, or an existing inbox report, already covers it.

The 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.

### Close out

**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.

## Disqualifiers (skip these)

- **Reporting currency just changed** — apparent step-change in all charts; not a regression. A `pattern:` scratchpad entry from a prior run usually flags this.
- **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.
- **Sandbox / test Stripe source** — `prefix` like `test_` or `sandbox_` means the team is wiring up integration; failures here aren't production signal.
- **Revenue event removed or renamed by the team** — `revenue_analytics_config.events[].eventName` from `project-get` no longer lists the "missing" event. Treat a new event name as a rename only when prior-run memory or other evidence links it to the old name. A second configured event can be independent, so an old event that stays in the config is still in scope.

When in doubt, write a memory entry instead of authoring a report.

## MCP tools

Direct calls (read-only):

- `project-get` — call without `id`. `revenue_analytics_config.events[]` and `revenue_analytics_config.filter_test_accounts` are the team's revenue config. If it fails, use the managed-view fallback in [Read the revenue config](#read-the-revenue-config) and state its limits.
- `external-data-sources-list` / `external-data-sources-retrieve` — Stripe source health. Filter `source_type` to payment platforms.
- `external-data-sync-logs` — failure history; one-off vs recurring upstream issues.
- `read-data-schema events` / `read-data-schema event_properties` — confirm revenue event + properties still flow.
- `query-trends` — validate event-volume drops with a 14-day window and weekly comparison.
- `execute-sql` against the managed views, which are the source of truth. There is no cross-source view. Each source has its own views, where `<kind>` is `charge`, `customer`, `mrr`, `product`, `revenue_item`, or `subscription`: `<source>.<prefix>.<kind>_revenue_view` (data warehouse, `<prefix>.` is absent when the source has no prefix) and `revenue_analytics.events.<event_name>.<kind>_events_revenue_view` (events). List them from `system.information_schema.tables`.
- `execute-sql` against `system.insights` / `system.dashboards` — find revenue insights and dashboards that depend on a failing source (blast radius).
- `dashboards-get-all` / `dashboard-get` — the built-in revenue dashboard and any custom revenue dashboards.
- `health-issues-list` — platform-detected issues on warehouse sources, where revenue is one of the highest-priority downstream consumers. Pass `kind="external_data_failure"`, `status="active"` and `dismissed=false` on every call: the endpoint excludes nothing by default, so without all three you rank resolved rows and ones a human already waved off. It serves 50 rows by default (250 max) ordered severity-first, so read `count` and page with `offset` when it exceeds the rows you hold.

Harness-level:

- `scout-project-profile-get` / `scout-scratchpad-search` / `scout-runs-list` / `scout-runs-retrieve` — orientation + dedupe.
- `inbox-reports-list` / `inbox-reports-retrieve` — find an existing report before authoring.
- `scout-emit-report` / `scout-edit-report` — author a report / edit an existing one (the report-channel contract is in the harness prompt).
- `scout-members-list` — this project's members with their resolved `github_login`, for `suggested_reviewers` routing.
- `scout-scratchpad-remember` — durable memory across runs.

For 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).

## When to stop

- No payment platform + empty `revenue_analytics_config.events` → close out empty (after writing the `not-in-use:` scratchpad entry).
- Profile + scratchpad show a stable picture → close out empty.
- A candidate matches a scratchpad entry with `noise:` / `addressed:` / `dedupe:` key prefix → skip.
- 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.

"Looked but found nothing meaningful" is a real outcome.

From posthog/posthog at 244c70d, shown as plain text under its license: MIT (permissive). The license text is in LICENSE.

View SKILL.md on GitHub at 244c70d

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