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 majiayu000/spellbook --skill product-analyticsgit clone --depth 1 https://github.com/majiayu000/spellbookWrote 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/majiayu000/spellbook/product-analytics)<a href="https://agentmods.dev/skills/majiayu000/spellbook/product-analytics"><img src="https://agentmods.dev/badge/skills/majiayu000/spellbook/product-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/majiayu000/spellbook/product-analytics"><img src="https://agentmods.dev/badge/skills/majiayu000/spellbook/product-analytics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00043 | $0.02825 |
| Opus 5 | $0.00022 | $0.01412 |
| Sonnet 5 | $0.00009 | $0.00565 |
| Haiku 4.5 | $0.00004 | $0.00282 |
Grade A, and why
product-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 6d 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 — 458 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Analytics
Core Principles
- Metrics over vanity — Focus on actionable metrics tied to business outcomes
- Data-driven decisions — Hypothesize, measure, learn, iterate
- User-centric measurement — Track behavior, not just pageviews
- Statistical rigor — Understand significance, avoid false positives
- Privacy-first — Respect user data, comply with GDPR/CCPA
- North Star focus — Align all teams around one key metric
Hard Rules (Must Follow)
These rules are mandatory. Violating them means the skill is not working correctly.
No PII in Events
Events must NEVER contain personally identifiable information.
// ❌ FORBIDDEN: PII in event properties
track('user_signed_up', {
email: '[email protected]', // PII!
name: 'John Doe', // PII!
phone: '+1234567890', // PII!
ip_address: '192.168.1.1', // PII!
credit_card: '4111...', // NEVER!
});
// ✅ REQUIRED: Anonymized/hashed identifiers only
track('user_signed_up', {
user_id: hash('[email protected]'), // Hashed
plan: 'pro',
source: 'organic',
country: 'US', // Broad location OK
});
// Masking utilities
const maskEmail = (email) => {
const [name, domain] = email.split('@');
return `${name[0]}***@${domain}`;
};
Object_Action Event Naming
All event names must follow the object_action snake_case format.
// ❌ FORBIDDEN: Inconsistent naming
track('signup'); // No object
track('newProject'); // camelCase
track('Upload File'); // Spaces and PascalCase
track('user-created'); // kebab-case
track('BUTTON_CLICKED'); // SCREAMING_CASE
// ✅ REQUIRED: object_action snake_case
track('user_signed_up');
track('project_created');
track('file_uploaded');
track('payment_completed');
track('checkout_started');
Actionable Metrics Only
Track metrics that drive decisions, not vanity metrics.
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.
- 6d ago First seen · 458 lines · 43 tokens per session scan A c3684f6c5cdf
product-analytics is a skill published in the GitHub repository majiayu000/spellbook (277 stars, last pushed yesterday), licensed MIT. It adds 43 tokens to every session and 2,825 once invoked, about $0.0002 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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