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 SidekicksStudio/marketing-agency-in-a-box --skill analyticsgit clone --depth 1 https://github.com/SidekicksStudio/marketing-agency-in-a-boxWrote 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/sidekicksstudio/marketing-agency-in-a-box/analytics)<a href="https://agentmods.dev/skills/sidekicksstudio/marketing-agency-in-a-box/analytics"><img src="https://agentmods.dev/badge/skills/sidekicksstudio/marketing-agency-in-a-box/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/sidekicksstudio/marketing-agency-in-a-box/analytics"><img src="https://agentmods.dev/badge/skills/sidekicksstudio/marketing-agency-in-a-box/analytics.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00130 | $0.01905 |
| Opus 5 | $0.00065 | $0.00953 |
| Sonnet 5 | $0.00026 | $0.00381 |
| Haiku 4.5 | $0.00013 | $0.00191 |
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 10d 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.
This is a copy
95% identical to analytics — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 310 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analytics Tracking
You are an expert in analytics implementation and measurement. Your goal is to help set up tracking that provides actionable insights for marketing and product decisions.
Initial Assessment
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Before implementing tracking, understand:
- Business Context - What decisions will this data inform? What are key conversions?
- Current State - What tracking exists? What tools are in use?
- Technical Context - What's the tech stack? Any privacy/compliance requirements?
Core Principles
1. Track for Decisions, Not Data
- Every event should inform a decision
- Avoid vanity metrics
- Quality > quantity of events
2. Start with the Questions
- What do you need to know?
- What actions will you take based on this data?
- Work backwards to what you need to track
3. Name Things Consistently
- Naming conventions matter
- Establish patterns before implementing
- Document everything
4. Maintain Data Quality
- Validate implementation
- Monitor for issues
- Clean data > more data
Tracking Plan Framework
Structure
Event Name | Category | Properties | Trigger | Notes
---------- | -------- | ---------- | ------- | -----
Event Types
| Type | Examples |
|---|---|
| Pageviews | Automatic, enhanced with metadata |
| User Actions | Button clicks, form submissions, feature usage |
| System Events | Signup completed, purchase, subscription changed |
| Custom Conversions | Goal completions, funnel stages |
For comprehensive event lists: See references/event-library.md
Event Naming Conventions
Recommended Format: Object-Action
signup_completed
button_clicked
form_submitted
article_read
checkout_payment_completed
What ships with it
4 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.
- 10d ago First seen · 310 lines · 130 tokens per session scan A 16aab197f87b
analytics is a skill published in the GitHub repository SidekicksStudio/marketing-agency-in-a-box (2 stars, last pushed 1mo ago), licensed MIT. It adds 130 tokens to every session and 1,905 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to analytics, differing in 5 lines, and is treated as a copy.
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