analytics-product

Analytics de produto — PostHog, Mixpanel, eventos, funnels, cohorts, retencao, north star metric, OKRs e dashboards de produto.

Quality

68%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/analytics-product/SKILL.md

Quality

Content

67%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 body with strong executable examples across the product-analytics workflow and a thoughtful limitations section. Its main weaknesses are minor redundancy/padding in the framing sections and a few incomplete code references.

Suggestions

Remove the duplicated 'Decida com Dados' heading, the verbatim repeat of the description in Overview, and the decorative Deming quote to tighten the opening.

Define or stub 'calculate_wow_growth' (and move the '## Uso:' usage note out of the Python code block) so the Posthog/north-star examples are copy-paste runnable.

Consider splitting the longer reference-style code (cohort retention, significance calculator) into a references/ file with a one-line pointer from SKILL.md to improve progressive disclosure.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with executable code and explicitly-labeled illustrative examples, but there is notable padding — the title 'Decida com Dados' and the overview line repeat the description verbatim, plus a decorative Deming quote — that could be trimmed.	3 / 5
Actionability	Provides multiple concrete, mostly-executable code blocks (Posthog tracking, pandas cohort retention, north-star SQL, scipy A/B significance) with only minor gaps such as the undefined 'calculate_wow_growth' and a '## Uso:' line embedded inside a Python block.	4 / 5
Workflow Clarity	The funnel-optimization section gives a clear 6-step sequence (Identificar→Entender→Hipotese→Testar→Medir→Aprender) with guardrail/SRM checkpoints, and the A/B guidance requires pre-specifying unit, metric, window, and stopping rule; minor validation gaps remain but no destructive batch operation is involved.	4 / 5
Progressive Disclosure	Single-file skill with well-organized section headers and one signaled external link (PostHog Python docs); no bundle files exist to verify. Structure is good, though several large inline code blocks (cohort, north star, significance) could optionally live in separate reference files.	4 / 5
	Total	15 / 20 Passed

Description

70%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.

A specific, well-targeted description that lists concrete tools and product-analytics concepts, but it omits any explicit 'when to use' trigger guidance, which caps completeness. Third-person voice is preserved and there is no vague fluff.

Suggestions

Append an explicit trigger clause, e.g. 'Use when configuring event tracking, building conversion funnels, analyzing cohort retention, defining a north star metric, or setting up product OKRs/dashboards.'

Add a few high-intent synonyms that currently live only in the body ('A/B testing', 'feature flags', 'DAU/MAU') to broaden natural trigger coverage.

Reframe one or two items as actions (e.g. 'instrument events', 'analyze funnels') to strengthen the specificity anchor toward 5.

Dimension	Reasoning	Score
Specificity	Names the domain plus many concrete items — 'PostHog, Mixpanel, eventos, funnels, cohorts, retencao, north star metric, OKRs e dashboards' — giving specific coverage, though these are topics/tools rather than verb-form actions, so it sits below the comprehensive-action anchor 5.	4 / 5
Completeness	Has a clear 'what' (analytics de produto + enumerated capabilities) but no 'Use when...' or equivalent trigger guidance, so per the rubric it is capped at 3.	3 / 5
Trigger Term Quality	Includes natural product-analytics terms users would say ('funnels, cohorts, retencao, north star metric, OKRs, dashboards') with good coverage, but lacks some synonyms/variations (e.g. 'A/B testing', 'feature flags') that appear only in the body.	4 / 5
Distinctiveness Conflict Risk	The named tools (PostHog, Mixpanel) and product-analytics framing carve a clear niche with distinct triggers and minimal overlap risk with other skills.	5 / 5
	Total	16 / 20 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: sickn33/agentic-awesome-skills
Path: skills/analytics-product/SKILL.md
Commit: b1aebac

Reviewed: ~19 hours ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.