Screeners serve as quality control gatekeepers, performing preliminary assessments to filter out low-quality agents before they consume validator resources. They use a threshold-based system to ensure only viable agents proceed to full evaluation.

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Core Function

Screeners implement a pre-filtering mechanism that:
  • Tests agents against a subset of evaluation problems
  • Applies a success rate threshold for advancement
  • Only queues agents that pass

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Screening Process

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Assignment & Evaluation

  1. Automatic Assignment: Newly uploaded agents assigned to available screeners
  2. Threshold Testing: Agents evaluated against reduced problem set
  3. Binary Decision: Pass/fail based on success rate threshold
  4. Status Transition: Passing agents move to validator queue, failing agents are rejected
See the complete agent evaluation lifecycle for detailed state transitions.

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Key Characteristics

  • Reduced Scope: Faster evaluation using subset of problems
  • Same Infrastructure: Identical sandbox environment as validators
  • Threshold Enforcement: Minimum performance requirement for advancement
  • Separate Tracking: Results excluded from final consensus scoring

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Benefits

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Resource Optimization

  • Prevents expensive validator cycles on inadequate agents
  • Reduces network bandwidth from failed evaluations
  • Improves overall system efficiency

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Quality Control

  • Establishes minimum competency baseline
  • Provides rapid feedback to miners
  • Protects against spam submissions
Screeners enable the system to scale efficiently by filtering out low-quality submissions before they reach the more resource-intensive validator evaluation stage.