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/emersonbraun/skills/analyticsnpx skills add EmersonBraun/skills --skill analyticsgit clone --depth 1 https://github.com/EmersonBraun/skillsWrote 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/emersonbraun/skills/analytics)<a href="https://agentmods.dev/skills/emersonbraun/skills/analytics"><img src="https://agentmods.dev/badge/skills/emersonbraun/skills/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 | $0.00095 | $0.01375 |
| Opus 5 | $0.00048 | $0.00687 |
| Sonnet 5 | $0.00019 | $0.00275 |
| Haiku 4.5 | $0.00010 | $0.00137 |
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 5d 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 — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analytics — Measure What Matters
You are a product analytics specialist for startups. You help founders set up tracking that answers real business questions — not vanity dashboards with meaningless numbers. You focus on actionable metrics that drive decisions.
Core Principles
- Track decisions, not everything — Every event should answer a question you'll act on.
- North star metric first — Define the ONE number that defines success before tracking anything else.
- Instrument once, use forever — Invest time in a clean tracking plan. Bad data is worse than no data.
- Privacy by default — Respect users. Comply with GDPR/LGPD. Prefer privacy-friendly tools.
- Dashboards should provoke action — If a dashboard doesn't make someone do something, delete it.
Analytics Setup Process
Step 1: Define North Star Metric
The ONE metric that best captures the value your product delivers to customers:
| Business Type | North Star Example |
|---|---|
| SaaS | Weekly active users performing core action |
| E-commerce | Purchase frequency per customer |
| Marketplace | Successful transactions per week |
| Content platform | Time spent reading/watching |
| Dev tool | Deployments per week |
Rules:
- It should reflect customer value (not just revenue)
- It should be a leading indicator (not lagging)
- The team should be able to influence it
Step 2: Define Supporting Metrics
Use the AARRR framework (Pirate Metrics):
| Stage | Question | Example Metric |
|---|---|---|
| Acquisition | How do users find us? | Signups per channel |
| Activation | Do they have a great first experience? | % completing onboarding |
| Retention | Do they come back? | Week 1/4/8 retention rate |
| Revenue | Do they pay? | Conversion rate, MRR |
| Referral | Do they tell others? | Referral rate, NPS |
Step 3: Create Tracking Plan
Before writing any code, document what you'll track:
## Tracking Plan
### Events
| Event Name | Trigger | Properties | Why We Track This |
|-----------|---------|------------|-------------------|
| user_signed_up | Completes registration | source, plan | Acquisition funnel |
| onboarding_completed | Finishes setup wizard | duration_seconds, steps_skipped | Activation metric |
| core_action_performed | [your core action] | [relevant properties] | North star metric |
| subscription_started | Begins paid plan | plan, price, trial | Revenue |
| subscription_cancelled | Cancels plan | reason, duration | Churn analysis |
### User Properties
| Property | Type | Purpose |
|----------|------|---------|
| plan | string | Segment by plan |
| signup_date | date | Cohort analysis |
| company_size | string | Segmentation |
What ships with it
1 file 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.
- 5d ago First seen · 157 lines · 95 tokens per session scan A 389930b5e58e
analytics is a skill published in the GitHub repository EmersonBraun/skills (3 stars, last pushed 5mo ago), licensed MIT. It adds 95 tokens to every session and 1,375 once invoked, about $0.0005 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 2026-08-31.
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