Policy Queries

Query Zubbl for optimized task strategies before execution.

Usage

policy = zubbl.query(task_description="code review")

if policy:
    print(f"Task: {policy.task_type}")
    print(f"Confidence: {policy.confidence_score}")
    print(f"Actions: {policy.recommended_actions}")

How Policies Work

1. Zubbl analyzes all past trajectories for the given task type
2. Patterns are scored by success rate, efficiency, and feedback
3. Top patterns are returned as policy recommendations
4. Your agent uses these to guide its approach

Scoring Factors

Factor	Weight	Description
Success Rate	40%	Historical success of the pattern
Token Efficiency	30%	Lower token usage = better
Latency	20%	Faster execution = better
Feedback	10%	Human/automated ratings