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 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/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/ericrisco/rsc-harness/analytics"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/analytics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Excessive Agency · line 193 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00080 | $0.02892 |
| Opus 5.5 | $0.00032 | $0.01157 |
| Sonnet 5.5 | $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 1mo 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.
- 1mo ago First seen · 198 lines · 80 tokens per session scan A ad80b408ba37
analytics is a skill published in the GitHub repository ericrisco/rsc-harness (227 stars, last pushed today), licensed MIT. It adds 80 tokens to every session and 2,892 once invoked, about $0.0003 per session on Opus 5.5. 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.
Other skills, from other repositories
managing-mcp-servers
Use when the user asks to add, change, remove, enable or disable an MCP server, or when an MCP tool is missing, needs sign-in, fails, or was blocked. ThinkRail runs pi in-process, so there is no pi command to call.
todos
Use when the user asks for a shared plan, a task needs at least three substantive execution steps, or a loose TODO is pending. Without an explicit plan request, not for one-shot answers or checks, or one- to two-step work that is not already in the list.
writing-workflow-skills
Use when adding a new workflow skill to pi-thinkrail-workflow, changing an existing workflow skill's role, trigger, handoff, or structure, or checking a workflow skill against the workflow system's rules. Not for authoring general-purpose skills outside this package.
writing-specs
Use when a workflow step drafts or revises a spec artifact — a goal-and-requirements, an architecture, or a module SPEC — or when a workflow skill names it at such a step. The shared quality bar for specs — not a workflow, nothing to execute.
setting-up-a-project
Use when asked to set up, onboard, initialize, or spec a project with no spec graph, or when invoked by the app's Set-up-project card. Not for ordinary work in an already-specced project.
release-notes
Write release notes for a tagged release — a business-impact summary of what changed for the user, plus a thanks section naming every contributor whose commits are in the release. Short by construction.