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ThinkingAIAgenticEngineThinkingAIAgenticEngine/scenario-skills/skills/retention/new-user-analysis/SKILL.md

new-user-analysis

Skill6 starsChanged 30 days agoNo licenceView on GitHub

Trigger when the user asks to analyze new-user quality, first-day behavior, new-user retention/churn, channel quality for new users, or structural changes in newly acquired users. The Skill first asks the user to confirm the new-user definition (caliber), analysis dimensions, product type, and time range, then validates event/property metadata and sample quality before querying business data. It scores first-day quality (engagement depth, feature adoption, monetization readiness, retention signal), analyzes first-day behavior paths and funnels, attributes D1/D3/D7 retention to first-day behaviors and acquisition channels, and diagnoses structural mutations in the new-user mix. Use ae-cli event/path/retention/funnel/sql models and deliver Markdown or HTML reports depending on analysis depth. Do not trigger for existing-user retention/churn or requests to create a new/old user classification property.

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22 rules. About 0 are common, 17 are distinctive, and 5 are very specific to this project.

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    Many files like this have a rule of this kind.

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No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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