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Explains a health score drop — decomposes which score components moved, finds the triggering events, and recommends a proportionate response. Use when a health score fell, a risk alert fired, or someone asks "why did X's health drop".
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SOC 職業分類に基づく
Produces a full account snapshot on demand — profile, health, revenue, stakeholders, activity, and risks in one view. Use when someone asks "catch me up on X", "give me the full picture on X", or needs to get oriented on an account they don't know.
Identifies reference, case-study, and advocacy candidates — healthy, tenured accounts with strong outcomes and vocal fans. Use when marketing needs references, sales needs proof points for a vertical, or building an advocacy program.
Leadership-ready roll-up of at-risk accounts — who is at risk, why, how much ARR is exposed, and what's being done. Use for weekly risk reviews, leadership updates, or when asked "which accounts are at risk right now".
Responds to a champion or sponsor departure — maps the remaining relationship surface, assesses exposure, and builds a re-entry plan for the new stakeholder. Use when a key contact leaves, changes roles, or a new decision-maker inherits the account.
Deep-dives a red account and produces a structured save plan — root causes ranked, save plays matched to causes, and a realistic assessment of whether the account is savable. Use when an account turns red, gives churn signals, or someone says "we're going to lose X".
Performs a structured customer health review using usage data, support interactions, renewal signals, and stakeholder sentiment. Use when asked to assess customer health, identify churn risk, prepare for QBRs, or generate a health score.
| name | health-drop-diagnosis |
| description | Explains a health score drop — decomposes which score components moved, finds the triggering events, and recommends a proportionate response. Use when a health score fell, a risk alert fired, or someone asks "why did X's health drop". |
| license | MIT |
| compatibility | Tool calls resolve natively in Quivly, or in Claude Code / claude.ai / any MCP-enabled agent via the Quivly MCP connector. Without tools, the skill degrades to a guided manual workflow. |
| metadata | {"author":"quivly","version":"1.0","category":"customer-engineering","quivly-tools":"health.get-health-score health.get-insights platform-data.get-usage platform-data.search-tickets communication.search-conversations"} |
You explain a health score movement in plain language: which inputs moved, what real-world events drove them, and how worried to be.
Core principle: a health score is a smoke detector, not a diagnosis — never recommend action from the score alone; trace it to real events first.
get-health-score). Identify which components dropped and by how much — the composite hides the story.get-usage)search-tickets)search-conversations)get-insights) for events the score may lag: champion departure, funding news, org changes.Health drop: {Customer} — score before → after, severity verdict
What moved — component-by-component, each mapped to its real-world cause
The story — 2-3 sentences of narrative: what is actually happening at this account
Response — proportionate to severity: nothing (mechanical), targeted play (early warning), or escalate to save-plan mode (confirmed)
Related skills: usage component is the driver → usage-drop-investigation; confirmed risk → churn-save-plan; full structured review → customer-health-review.