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 agentmods add skills/ericrisco/rsc-harness/analyticsnpx skills add ericrisco/rsc-harness --skill analyticsgit clone --depth 1 https://github.com/ericrisco/rsc-harnessWrote 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/ericrisco/rsc-harness/analytics)<a href="https://agentmods.dev/skills/ericrisco/rsc-harness/analytics"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/analytics.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00080 | $0.02892 |
| Opus 5 | $0.00040 | $0.01446 |
| Sonnet 5 | $0.00016 | $0.00578 |
| Haiku 4.5 | $0.00008 | $0.00289 |
Grade A, and why
analytics 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 198 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analytics — the instrumentation layer
This skill owns the capture side of analytics: deciding what to track, how to name it, where the SDK lives in the codebase, and how not to leak PII or break consent law. It produces three checkable artifacts — an event taxonomy, tracking code (GA4 and/or PostHog), and a consent wiring. Everything downstream of capture (charts, KPI choice, experiment stats, raw-event SQL, legal text) belongs to a sibling; see the routing table below.
The order of work is fixed: taxonomy → SDK wiring → consent gate → PII scrub → funnel + validation.
When NOT to use
| The ask | Route to |
|---|---|
| Chart the captured data on a board | dashboard |
| Decide which metrics matter (North Star, AARRR) | kpi-framework |
| Scheduled stakeholder reports / exports | reporting |
| Variant assignment, significance, experiment design | ab-testing (PostHog experiments live there; PostHog event capture lives here) |
| Query a warehouse of raw events with SQL | clickhouse-analytics / duckdb / sql |
| App error/trace/uptime telemetry (Sentry, OpenTelemetry) | observability |
| Cookie-banner legal text, DPA, ROPA, subject rights | gdpr-privacy / data-policy |
| Predict future values from a series | forecasting |
The load-bearing line: analytics = events flow in; dashboard/reporting = events flow out.
Decision: GA4 vs PostHog vs both
| You need | Pick |
|---|---|
| Web/ads attribution, Google Ads conversions, marketing audiences | GA4 |
| Product behavior, funnels, feature flags, session replay, self-serve insights | PostHog |
| Both marketing attribution and deep product analytics (very common) | Both — GA4 for ads, PostHog for product |
Running both is normal and fine. Keep one taxonomy shared across both so a purchase means the same
thing everywhere. Do not let the two tools drift into two naming schemes.
Step 1 — Event taxonomy first, code second
An event name is a contract: design the taxonomy before you write a single SDK call, and never rename a
live event in production. Every funnel, audience, dashboard, and saved insight downstream is keyed by the
exact event name and property keys. Rename signup_completed to sign_up after launch and you silently
fork the metric into two — the old funnel flatlines, the new one starts from zero, and nobody notices for a
week. You can add events forever; you can never safely rename one.
What ships with it
6 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.
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.
- 4d ago First seen · 198 lines · 80 tokens per session scan A ad80b408ba37
analytics is a skill published in the GitHub repository ericrisco/rsc-harness (60 stars, last pushed today), licensed MIT. It adds 80 tokens to every session and 2,892 once invoked, about $0.0004 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 2026-08-30.
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