data-analytics

Skill para definicao de eventos, naming de tracking, funis, metricas de produto e instrumentacao analitica. Use quando precisar medir valor entregue, ativacao, conversao, retencao e comportamento do usuario. Trigger em: "tracking", "analytics", "eventos de produto", "funil de conversao", "instrumentar evento", "metrica de produto", "ativacao", "retencao", "naming de evento", "tracking plan", "data analytics", "PostHog", "Amplitude", "Mixpanel".

Quality

89%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

78%Weight 40%Scale 1-5

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

A well-structured, actionable analytics-instrumentation skill that earns high marks on actionability and conciseness. Main gaps are the lack of an explicit validation feedback loop in the workflow and references that are mentioned in prose rather than navigable pointers.

Suggestions

Promote the 'Evidencia de Conclusao' checklist into an explicit numbered workflow with a validate -> fix -> re-verify loop before the handoff step.

Consolidate external file references (GLOBAL.md, policies/*.md, templates/analytics-plan.md) into a single clearly signaled 'References' section with one-level-deep pointers rather than burying them in the governance paragraph.

Trim the rhetorical opening line and a few informal phrases to tighten conciseness toward a fully lean body.

Dimension	Reasoning	Score
Conciseness	Dense and competence-assuming with no basic-concept padding, but a few rhetorical flourishes ('Uma feature sem medicao e uma aposta sem placar', 'o que mais apodrece um projeto') could be trimmed to hit a fully lean 5.	4 / 5
Actionability	Highly actionable for an instruction-only skill: a concrete naming convention (object_action, snake_case, past tense) with good/bad comparison, a tracking-plan table with real events/properties/owners, and a server-vs-client firing rule quantified at 5-15% loss.	5 / 5
Workflow Clarity	Clear section sequence with a verification checklist ('Evidencia de Conclusao') and governance-mandated proof, but the validate->fix->retry feedback loop is only implied rather than explicitly interleaved in the main flow.	4 / 5
Progressive Disclosure	Sections are well organized, but no bundle files exist and the external file references (GLOBAL.md, policies/*.md, templates/analytics-plan.md) are buried in a governance sentence rather than clearly signaled as one-level-deep navigation.	3 / 5
	Total	16 / 20 Passed

Description

100%Weight 40%Scale 1-5

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 is exemplary: third-person, concise, and covers what/when with a rich, natural trigger-term list including tools. No notable weaknesses.

Dimension	Reasoning	Score
Specificity	Lists multiple distinct concrete actions across the analytics domain — 'definicao de eventos, naming de tracking, funis, metricas de produto e instrumentacao analitica' — giving comprehensive coverage rather than a single action.	5 / 5
Completeness	Explicitly answers both 'what' ('Skill para definicao de eventos...') and 'when' ('Use quando precisar medir valor entregue, ativacao, conversao, retencao...') with concrete trigger phrases.	5 / 5
Trigger Term Quality	An explicit 'Trigger em:' block provides comprehensive natural terms including synonyms ('tracking', 'data analytics', 'tracking plan'), behavior phrases ('ativacao', 'retencao', 'funil de conversao') and tool names ('PostHog', 'Amplitude', 'Mixpanel').	5 / 5
Distinctiveness Conflict Risk	Occupies a clear niche (product analytics instrumentation) with tool-specific triggers and a body that explicitly disambiguates from observability, SEO and closed-loop-revenue skills, keeping conflict risk minimal.	5 / 5
	Total	20 / 20 Passed

Validation

100%

Warnings & errors only

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: felvieira/claude-skills-fv
Path: skills/21-data-analytics/SKILL.md
Commit: f3492ef

Reviewed: 5 days ago

Table of Contents

Discovery Implementation Validation

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