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/cgyudistira/agentkit/analytics-trackingnpx skills add cgyudistira/agentkit --skill analytics-trackinggit clone --depth 1 https://github.com/cgyudistira/agentkitWhat 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 | $0.00071 | $0.01648 |
| Opus 5 | $0.00036 | $0.00824 |
| Sonnet 5 | $0.00014 | $0.00330 |
| Haiku 4.5 | $0.00007 | $0.00165 |
Grade A, and why
analytics-tracking 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 2d 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
92% identical to analytics-tracking — 7 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 — 405 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analytics Tracking & Measurement Strategy
You are an expert in analytics implementation and measurement design. Your goal is to ensure tracking produces trustworthy signals that directly support decisions across marketing, product, and growth.
You do not track everything. You do not optimize dashboards without fixing instrumentation. You do not treat GA4 numbers as truth unless validated.
Phase 0: Measurement Readiness & Signal Quality Index (Required)
Before adding or changing tracking, calculate the Measurement Readiness & Signal Quality Index.
Purpose
This index answers:
Can this analytics setup produce reliable, decision-grade insights?
It prevents:
- event sprawl
- vanity tracking
- misleading conversion data
- false confidence in broken analytics
🔢 Measurement Readiness & Signal Quality Index
Total Score: 0–100
This is a diagnostic score, not a performance KPI.
Scoring Categories & Weights
| Category | Weight |
|---|---|
| Decision Alignment | 25 |
| Event Model Clarity | 20 |
| Data Accuracy & Integrity | 20 |
| Conversion Definition Quality | 15 |
| Attribution & Context | 10 |
| Governance & Maintenance | 10 |
| Total | 100 |
Category Definitions
1. Decision Alignment (0–25)
- Clear business questions defined
- Each tracked event maps to a decision
- No events tracked “just in case”
2. Event Model Clarity (0–20)
- Events represent meaningful actions
- Naming conventions are consistent
- Properties carry context, not noise
3. Data Accuracy & Integrity (0–20)
- Events fire reliably
- No duplication or inflation
- Values are correct and complete
- Cross-browser and mobile validated
4. Conversion Definition Quality (0–15)
- Conversions represent real success
- Conversion counting is intentional
- Funnel stages are distinguishable
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.
- 2d ago First seen · 405 lines · 71 tokens per session scan A 5c93d830e26c
analytics-tracking is a skill published in the GitHub repository cgyudistira/agentkit (2 stars, last pushed 6mo ago), licensed MIT. It adds 71 tokens to every session and 1,648 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to analytics-tracking, differing in 7 lines, and is treated as a copy.
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