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analytics-tracking

Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data.

32

Quality

26%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./plugins/antigravity-awesome-skills/skills/analytics-tracking/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

20%Scale 1-3

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This skill reads more like a consulting framework or strategy document than an actionable skill for Claude. It is heavily conceptual, explaining analytics best practices that Claude already understands, without providing any executable code, concrete scoring mechanisms, or specific implementation examples. The phased structure provides some workflow clarity, but the lack of actionable specifics and extreme verbosity significantly reduce its utility.

Suggestions

Replace abstract descriptions with concrete, executable examples—e.g., show actual GTM dataLayer.push() code, a real GA4 event configuration, or a Python/JS validation script for detecting duplicate event firing.

Cut sections that explain concepts Claude already knows (what a conversion is, what PII means, basic privacy principles) and reduce the content by at least 50%.

Provide a concrete scoring methodology for the Measurement Readiness Index—e.g., a checklist with specific yes/no questions that map to point values, rather than abstract category descriptions.

Move detailed reference material (event taxonomy, UTM rules, GA4 guidance) into separate bundle files and reference them from the main SKILL.md to improve progressive disclosure.

DimensionReasoningScore

Conciseness

The skill is extremely verbose at ~300+ lines, explaining many concepts Claude already knows (what a conversion is, what UTMs are, basic privacy principles, what PII means). Extensive sections like 'Core Principles' and 'Privacy & Compliance' state obvious best practices. The scoring index framework, while structured, is largely conceptual padding without executable specifics.

1 / 3

Actionability

The skill provides no concrete code, commands, or executable examples. It describes what to do abstractly ('calculate the Measurement Readiness & Signal Quality Index') without showing how to actually calculate scores, audit implementations, or validate tracking. The GA4/GTM section says 'push clean dataLayer events' without showing a single dataLayer.push() example. Everything is descriptive rather than instructive.

1 / 3

Workflow Clarity

There is a clear phased structure (Phase 0 → Phase 1 → Design → Implementation) and the requirement to stop if the score is 'Broken' is a good checkpoint. However, the actual scoring process lacks concrete validation steps—how exactly does one score each category? There are no feedback loops for error recovery, and the validation section lists what to check without showing how.

2 / 3

Progressive Disclosure

The content references related skills (page-cro, ab-test-setup, etc.) which is good navigation. However, the massive amount of inline content (scoring rubric, event taxonomy, conversion strategy, UTM rules, privacy, compliance) should be split into separate reference files. With no bundle files, everything is crammed into one monolithic document.

2 / 3

Total

6

/

12

Passed

Description

32%Scale 1-3

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description identifies a clear domain (analytics tracking) and lists high-level actions, but lacks the specificity, trigger terms, and explicit 'Use when...' guidance needed for reliable skill selection. It reads more like a tagline than a functional description that would help Claude distinguish this skill from data analysis or general analytics skills.

Suggestions

Add an explicit 'Use when...' clause with trigger scenarios, e.g., 'Use when the user asks about event tracking, analytics instrumentation, tracking plans, data quality audits, or fixing broken analytics.'

Include specific concrete actions and deliverables, e.g., 'Creates tracking plans, validates event schemas, identifies tracking gaps, reviews analytics implementation code, and ensures data taxonomy consistency.'

Add natural trigger terms users would say, such as 'event tracking', 'tracking plan', 'analytics implementation', 'Google Analytics', 'Segment', 'Mixpanel', 'data quality', 'instrumentation'.

DimensionReasoningScore

Specificity

Names the domain (analytics tracking systems) and lists some actions (design, audit, improve), but these actions are fairly high-level and not deeply concrete. It doesn't specify what kinds of tracking, what tools, or what specific deliverables.

2 / 3

Completeness

Describes what the skill does (design, audit, improve analytics tracking systems) but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per rubric guidelines, a missing 'Use when...' clause caps completeness at 2, and the 'what' is also somewhat vague, warranting a score of 1.

1 / 3

Trigger Term Quality

Includes some relevant keywords like 'analytics', 'tracking', and 'audit', but misses common user terms like 'event tracking', 'Google Analytics', 'Mixpanel', 'UTM', 'data pipeline', 'instrumentation', 'telemetry', or 'metrics'. Users might phrase requests in many ways not covered here.

2 / 3

Distinctiveness Conflict Risk

The focus on 'analytics tracking systems' provides some specificity, but terms like 'analytics' and 'data' are broad enough to potentially overlap with data analysis, dashboard creation, or general data engineering skills.

2 / 3

Total

7

/

12

Passed

Validation

90%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

10

/

11

Passed

Repository
popey/claude-code-skills
Reviewed

Table of Contents

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