| name | predictive-action-intelligence |
| description | Use when designing proactive Dataverse recommendations such as churn risk, follow-up needs, API limit risks, compliance violations, pipeline risk, or next-best actions. Produces analysis design only. |
Predictive Action Intelligence
Purpose
Design proactive recommendations that detect Dataverse risks and suggest actions before users ask.
Use this skill for:
- pipeline risk analysis
- churn and follow-up recommendations
- flow/API limit risk warnings
- compliance risk detection
- stale record and process bottleneck detection
- next-best-action recommendations
V1 Boundary
This skill produces prediction and recommendation design guidance only. It does not train models, query Dataverse, monitor flows, or create alerts.
Workflow
- Define the prediction target and business outcome.
- Identify candidate signals from Dataverse records, relationships, status changes, activity history, flow runs, and process milestones.
- Define recommendation types: warn, explain, ask, create task, start workflow, escalate, or request approval.
- Define confidence, evidence, thresholds, false-positive handling, and user feedback capture.
- Define governance: who can see predictions, when action requires approval, and how explanations are logged.
Output Format
Return:
Prediction scenario: risk or opportunity to detect.Signals: data and process indicators to inspect.Recommendation model: suggested actions and confidence thresholds.Explainability: evidence and rationale shown to the user.Governance: visibility, approvals, feedback, and audit.
