{
  "name": "three-tier-evaluation-pipeline",
  "version": "1.0.0",
  "goal": "Run tasks through three evaluation tiers (Run, Trace, Thread) to produce comprehensive reports with human-in-the-loop validation",
  "inputs": [
    "query/input text for the task",
    "search results (for trace tier evaluation)",
    "evaluation criteria and thresholds"
  ],
  "steps": [
    "Step 1: Execute the main task using the Run tier of the evaluation pipeline (agentkit/runtime/LangGraph engine) to generate initial outputs and results",
    "Step 2: Run the Trace tier where an LLM-as-Judge evaluates the output against defined criteria, generating detailed analysis and scoring",
    "Step 3: Execute the Thread tier which facilitates human-in-the-loop discussion, approval, and iterative refinement of the output"
  ],
  "outputs": [
    "Final consolidated report combining results from all three tiers",
    "Detailed scores and metrics per tier",
    "Threaded discussion logs for human review and approval"
  ],
  "failure_modes": [
    "If the Run tier fails (e.g., code execution error), the pipeline can retry but may produce incomplete outputs",
    "If the Trace tier LLM-as-Judge produces low-quality evaluations, the Thread tier may need additional human intervention",
    "Threshold mismatches between tiers could cause the pipeline to exit early or require manual adjustment"
  ],
  "confidence": 0.95,
  "explanation": "The AgentKit repository contains a production-ready three-tier evaluation pipeline (Run \u2192 Trace \u2192 Thread) that can be adapted to any task requiring multi-stage validation. This workflow uses LangGraph for orchestration and LangChain for tool integration, making it portable across different agent engineering scenarios. The pattern is reusable because it separates concerns into distinct stages with clear inputs/outputs, allowing teams to plug in different evaluation criteria or human reviewers as needed.",
  "source_repo": "https://github.com/itszhaoziyan-n/AgentKit.git",
  "score": 1.0
}