Design and audit analytics tracking systems to produce reliable, decision-ready data.
Works with
Provides a Measurement Readiness & Signal Quality Index (0–100 score) to diagnose whether analytics setup can produce trustworthy insights before optimization or major decisions
Covers event model design, naming conventions, conversion definition, and property strategy to prevent event sprawl, vanity tracking, and inflated metrics
Includes validation guidance for real-time verification, duplica
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionanalytics-trackingExecute the skills CLI command in your project's root directory to begin installation:
Fetches analytics-tracking from sickn33/antigravity-awesome-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate analytics-tracking. Access via /analytics-tracking in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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.
Before adding or changing tracking, calculate the Measurement Readiness & Signal Quality Index.
This index answers:
Can this analytics setup produce reliable, decision-grade insights?
It prevents:
This is a diagnostic score, not a performance KPI.
| 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 |
| Score | Verdict | Interpretation |
|---|---|---|
| 85–100 | Measurement-Ready | Safe to optimize and experiment |
| 70–84 | Usable with Gaps | Fix issues before major decisions |
| 55–69 | Unreliable | Data cannot be trusted yet |
| <55 | Broken | Do not act on this data |
If verdict is Broken, stop and recommend remediation first.
(Proceed only after scoring)
If no decision depends on it, don’t track it.
Define:
Then design events.
Avoid:
Prefer:
Fewer accurate events > many unreliable ones.
Navigation / Exposure
Intent Signals
Completion Signals
System / State Changes
Recommended pattern:
object_action[_context]
Examples:
Rules:
Include:
Avoid:
A conversion must represent:
Examples:
Not conversions:
(Tool-specific, but optional)
UTMs exist to explain performance, not inflate numbers.
Analytics that violate trust undermine optimization.
| Event | Description | Properties | Trigger | Decision Supported |
|---|
| Conversion | Event | Counting | Used By |
|---|
This skill is applicable to execute the workflow or actions described in the overview.
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
sickn33/antigravity-awesome-skills
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
Useful defaults in analytics-tracking — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: analytics-tracking is focused, and the summary matches what you get after install.
Keeps context tight: analytics-tracking is the kind of skill you can hand to a new teammate without a long onboarding doc.
analytics-tracking has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in analytics-tracking — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added analytics-tracking from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
analytics-tracking has been reliable in day-to-day use. Documentation quality is above average for community skills.
analytics-tracking fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend analytics-tracking for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for analytics-tracking matched our evaluation — installs cleanly and behaves as described in the markdown.
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