client-health-dashboard

Solid

Generates a comprehensive client health overview across all accounts. Reads CRM data, support tickets, usage metrics, billing, and engagement logs. Calculates health scores, trend direction, and RAG status per client. Outputs a sorted risk report with recommended actions.

AI & Automation 288 stars 46 forks Updated 1 months ago MIT

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Skill Content

# Client Health Dashboard Generate a data-driven client health report: pull data from every available source, compute a weighted health score per client, and produce a prioritized risk report (`client-health-report.md`) sorted by risk with RAG status and actionable recommendations. ## Contents - `references/data-sources.md` -- what to pull from CRM, support, usage, billing, and communication channels - `references/scoring-model.md` -- dimensions, weights, scoring rules, composite formula, RAG thresholds, trend logic - `references/risk-and-recommendations.md` -- risk factor triggers, per-dimension recommendation menus, expansion assessment - `references/output-format.md` -- exact report structure, formatting rules, and missing-data handling ## Workflow 1. Collect data from every available source. Handle failures gracefully: log what was unavailable and proceed with partial data. Never fabricate data. See `references/data-sources.md` for the full source list and the fields to extract per client. 2. Score each client. Rate the five dimensions 0-100, apply weights, and compute the composite score. Assign RAG status and trend direction. See `references/scoring-model.md`. 3. Analyze risk and generate recommendations. Flag critical and warning risk factors, produce 2-4 specific recommendations targeting each client's weakest dimensions, and assess expansion potential for healthy accounts. See `references/risk-and-recommendations.md`. 4. Generate the report. Write `client-health...

Details

Author
OneWave-AI
Repository
OneWave-AI/claude-skills
Created
10 months ago
Last Updated
1 months ago
Language
Python
License
MIT

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