incomplete-onboarding-assessor

Classify incomplete onboardings by engagement temperature and generate a prioritized markdown report.

6|1|Updated Mar 5, 2026

Search Tags:#onboarding #analytics #engagement #reporting #sql #temperature #decay

Ready to run

npx skills add https://github.com/pwv-vc/agentcribs-community --skill incomplete-onboarding-assessor-pwv-vc

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: incomplete-onboarding-assessor
Source: https://github.com/pwv-vc/agentcribs-community/tree/main/resources/tearsheets/arsenal/dot-claude/skills/incomplete-onboarding-assessor
Command: npx skills add https://github.com/pwv-vc/agentcribs-community --skill incomplete-onboarding-assessor-pwv-vc

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill identifies and segments users who started onboarding but did not complete it, enabling targeted re-engagement based on engagement temperature and time decay.

Core Features & Use Cases

Temperature-based assessment: Classify incomplete onboardings into WARM, HOT, or COLD using engagement signals and decay rules.
Configurable window: Evaluate within a configurable days window (default 30 days) to balance recency and completeness.
Automated reporting: Generate a markdown assessment report with per-user details and a priority action list, saved to docs/.

Quick Start

Run the assess_onboardings.py script to generate a temperature-based assessment for incomplete onboardings.

Frequently Asked Questions about incomplete-onboarding-assessor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I identify incomplete onboardings and prioritize user re-engagement?▼

Identify incomplete onboardings by querying chat history and classifying engagement temperature. The tool computes original and current temperatures using decay rules, generating a prioritized markdown action plan for targeted re-engagement.

How does engagement temperature decay work for inactive onboarding users?▼

Engagement temperature decay applies time-based rules to downgrade user temperature from HOT or WARM to COLD. It evaluates chat history within a configurable days window, calculating current temperature to reflect diminishing user interest over time.

What's the best way to generate an onboarding analytics report for incomplete users?▼

Generate an onboarding analytics report by running the assessment script, which retrieves chat history and computes engagement temperatures. It outputs a markdown file containing per-user details and a priority action list saved to the docs directory.

Can I configure the time window for evaluating incomplete onboarding engagement?▼

You can configure the time window for evaluating incomplete onboardings by setting the days parameter. The default window is 30 days, which balances recency of user engagement signals with completeness of the analytics reporting.

How do I classify incomplete onboardings into WARM HOT or COLD engagement segments?▼

Classify incomplete onboardings by retrieving chat history and applying time-decay rules to engagement signals. The assessment script computes original and current temperatures, segmenting users into WARM, HOT, or COLD categories for prioritized re-engagement planning.

Does incomplete onboarding assessment work without external database dependencies?▼

The incomplete onboarding assessment runs as a standalone script with no external dependencies. It queries onboardings directly, retrieves chat history, computes temperature decay, and saves the markdown report locally to the docs folder.