client-health-dashboard

v2026.09.24

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.

GitHub
Install command
npx skhub add onewave-ai/client-health-dashboard
Markdown
SKILL.md

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-report.md following the exact structure and formatting rules. Handle missing data by scoring neutral (50) and noting gaps. See references/output-format.md.
  5. 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.
Discovery
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Version
Latest version metadata

Version

v2026.09.24

Published

Sep 24, 2026

Category

Uncategorized

License

MIT

Source path

client-health-dashboard

Default branch

main

Latest commit

f317e08

Tree SHA

5eb00f2