Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add PostHog/posthog-foss --skill modeling-revenue-metricsgit clone --depth 1 https://github.com/PostHog/posthog-fossWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/posthog/posthog-foss/modeling-revenue-metrics)<a href="https://agentmods.dev/skills/posthog/posthog-foss/modeling-revenue-metrics"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/modeling-revenue-metrics/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/posthog/posthog-foss/modeling-revenue-metrics"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/modeling-revenue-metrics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Prompt Injection · line 48 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 55 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 95 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00231 | $0.01620 |
| Opus 5 | $0.00115 | $0.00810 |
| Sonnet 5 | $0.00046 | $0.00324 |
| Haiku 4.5 | $0.00023 | $0.00162 |
Grade A, and why
modeling-revenue-metrics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- modeling-revenue-metrics — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Modeling revenue metrics
Turn payment/subscription data into durable revenue models. Read modeling-warehouse-foundations first for
the view-vs-dbt decision, the view-* workflow, and convertCurrency(); this skill is the revenue-specific
layer on top. Metric definitions live in
references/revenue-metric-definitions.md; copy-paste recipes in
references/posthog/ and references/dbt/.
Step 1 — find where revenue lives
Revenue reaches PostHog two ways; both feed the same managed revenue_analytics_* views:
- A payment platform as a warehouse source — Stripe today (Chargebee/Polar/RevenueCat coming). Best when
the business runs on a billing platform. Connect via
setting-up-a-data-warehouse-source. - Custom revenue events — you send events (e.g.
purchase_completed) with a revenue property. Best when there's no supported platform or you already track revenue in-product.
If neither exists yet, use suggesting-data-imports to recommend a source. In dbt, the equivalent is
staging whichever billing tables landed in the warehouse.
Step 2 — model on the managed views, not raw tables
PostHog auto-generates a curated set of views per source. Do not re-derive revenue from raw Stripe tables — the managed views already handle deferred-revenue recognition, currency, and a stable schema.
Discover the exact names (they're prefixed by source, e.g. stripe.<prefix>.…, plus a cross-source
revenue_analytics.all.…):
SELECT table_name FROM system.information_schema.tables WHERE table_name ILIKE '%revenue_analytics%'
| Managed view | Grain | Use for |
|---|---|---|
revenue_item (start here) |
1 / invoice line item | Gross revenue, monthly recurring revenue, revenue by product/customer/period. Implements deferred revenue + currency. |
mrr |
1 / (customer, subscription) | Live snapshot of current MRR — not a time series. |
customer |
1 / customer | dim_customer: email, country, cohort, metadata. |
subscription |
1 / subscription | Subscription state for churn/expansion logic. |
charge |
1 / charge | Raw charges; prefer revenue_item unless you specifically need charges. |
product |
1 / product | Product dimension. |
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/dbt/_sources_stripe.yml 862 B
- references/dbt/dim_customer.sql 324 B
- references/dbt/fct_mrr.sql 1.9 KB
- references/dbt/fct_revenue_item.sql 2.7 KB
- references/dbt/schema.yml 1.1 KB
- references/posthog/gross_revenue_by_month.sql 595 B
- references/posthog/mrr_and_arr.sql 1.1 KB
- references/posthog/revenue_by_customer.sql 1.1 KB
- references/revenue-metric-definitions.md 5.5 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 106 lines · 231 tokens per session scan A 854dd89f8dc9
modeling-revenue-metrics is a skill published in the GitHub repository PostHog/posthog-foss (715 stars, last pushed today), licensed MIT. It adds 231 tokens to every session and 1,620 once invoked, about $0.0012 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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