Client health dashboard
172 production-ready Claude Code skills for sales, marketing, design, engineering, and AI agent architecture. Built and maintained by OneWave AI.
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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.
SKILL.md
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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 channelsreferences/scoring-model.md-- dimensions, weights, scoring rules, composite formula, RAG thresholds, trend logicreferences/risk-and-recommendations.md-- risk factor triggers, per-dimension recommendation menus, expansion assessmentreferences/output-format.md-- exact report structure, formatting rules, and missing-data handling
Workflow
- 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.mdfor the full source list and the fields to extract per client. - 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. - 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. - Generate the report. Write
client-health-report.mdfollowing the exact structure and formatting rules. Handle missing data by scoring neutral (50) and noting gaps. Seereferences/output-format.md. - Validate before finalizing:
- Verify RAG assignments match score ranges.
- Confirm section ordering and within-section sorting.
- Confirm every client appears exactly once.
- Confirm each client has 2-4 specific, actionable recommendations.
- Attribute each data point to its source.
- Mark data gaps explicitly; never invent data that was not retrieved.
Interaction
- If the user specifies particular clients, filter the report to those only.
- If the user specifies a data source, prioritize it.
- If the user provides CSV/Excel files, parse them as a primary source.
- If the user requests a format variation, adapt accordingly.
- Confirm the output path before writing.
- If no data sources are accessible, explain what is needed and what to provide.
Constraints
- Never fabricate or hallucinate data; report only what was retrieved, attributed to its source.
- Never include credentials, API keys, or PII beyond business contact info.
- Keep health scores mathematically correct per the weighting formula.
- Keep recommendations specific and actionable, not generic.
- Keep the report self-contained, professional, and direct.
- Do not use emojis anywhere in the report or any output.