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.
55
44%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/21-data-analytics/SKILL.mdQuality
Discovery
67%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 covers a clear product analytics domain with both 'what' and 'when' clauses, which is a strength. However, the capability descriptions lean toward category labels rather than concrete actions, and the trigger terms could be broader to capture more natural user queries. The skill is reasonably distinctive but could benefit from sharper differentiation from adjacent product management or data analysis skills.
Suggestions
Replace category labels with more concrete actions, e.g., 'Define event schemas, create tracking naming conventions, design conversion funnels, specify product KPIs, and generate instrumentation plans'.
Add common English and Portuguese trigger term variations users might naturally say, such as 'analytics plan', 'tracking plan', 'event taxonomy', 'product KPIs', 'Mixpanel', 'Amplitude', or 'plano de instrumentação'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (product analytics/tracking) and lists some actions like 'definicao de eventos, naming de tracking, funis, metricas de produto e instrumentacao analitica', but these are more category labels than concrete specific actions (e.g., doesn't say 'create event schemas' or 'generate tracking plans'). | 2 / 3 |
Completeness | Clearly answers both 'what' (event definition, tracking naming, funnels, product metrics, analytical instrumentation) and 'when' with an explicit 'Use quando' clause specifying triggers like measuring delivered value, activation, conversion, retention, and user behavior. | 3 / 3 |
Trigger Term Quality | Includes relevant terms like 'eventos', 'tracking', 'funis', 'metricas de produto', 'ativacao', 'conversao', 'retencao', which are natural terms in the product analytics domain. However, it misses common variations and English equivalents that users might use (e.g., 'analytics', 'event tracking', 'funnel analysis', 'KPIs', 'Mixpanel', 'Amplitude'). | 2 / 3 |
Distinctiveness Conflict Risk | The focus on product analytics instrumentation and event tracking is fairly specific, but terms like 'metricas de produto' and 'comportamento do usuario' could overlap with general product management or UX research skills. The niche is identifiable but not sharply delineated. | 2 / 3 |
Total | 9 / 12 Passed |
Implementation
22%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 metadata/checklist template than actionable guidance. It lacks concrete examples of event naming conventions, sample funnel definitions, or specific analytics plan structures that would make it truly useful. The content tells Claude what to produce but never shows how, making it largely abstract and non-actionable.
Suggestions
Add concrete examples of event naming conventions (e.g., 'user_signed_up', 'button_clicked_checkout') with a sample event schema showing properties, types, and descriptions.
Include a step-by-step workflow: 1) Identify business objective → 2) Map user flow → 3) Define funnel stages → 4) Name events → 5) Validate coverage against objectives, with explicit validation checkpoints.
Provide a concrete example of a complete analytics plan for a sample feature (e.g., onboarding flow) showing the funnel, events, properties, and success metrics.
Add a sample naming convention table or pattern (e.g., 'object_action' format) with do/don't examples to make the 'verbo + objeto' guidance actionable.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is relatively lean and avoids explaining basic concepts, but some sections like 'Quando Usar' vs 'Quando Nao Usar' and the checklists are somewhat generic and don't add much beyond what Claude could infer. The structure is efficient but the content itself is thin. | 2 / 3 |
Actionability | The skill provides no concrete examples, no executable code, no specific naming conventions, no example event schemas, no sample funnel definitions. It describes what should be done at a high level ('evento nomeado com verbo + objeto') but never shows a concrete example of an analytics plan, event naming pattern, or funnel mapping. | 1 / 3 |
Workflow Clarity | There is no sequenced workflow or multi-step process defined. The skill lists checklists and expected outputs but never describes the order of operations, validation checkpoints, or how to iterate. For analytics instrumentation which involves multiple steps (define objectives → map funnel → name events → validate coverage), the absence of a clear sequence is a significant gap. | 1 / 3 |
Progressive Disclosure | The skill references external files like `policies/handoffs.md` and `templates/analytics-plan.md` which is good, but the references are minimal and not well-signaled with descriptions of what each contains. The main content itself is too thin to justify the split — the SKILL.md doesn't provide enough substance as an overview. | 2 / 3 |
Total | 6 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- felvieira/claude-skills-fv
- Commit
d87ad31
- Reviewed
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