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An outcome tells the session what the end result should look like and how to measure its quality. The agent works toward that target, self-evaluating and iterating until the outcome is met.
When you define an outcome, the harness automatically provisions a grader to evaluate the artifact against a rubric. The grader uses a separate context window to avoid being influenced by the main agent's implementation choices.
The grader returns an explanation summarizing which criteria passed or failed, or confirming that the artifact satisfies the rubric. That feedback is handed back to the agent for the next iteration.
A rubric is a markdown document describing per-criterion scoring. The rubric is required.
Example rubric:
# DCF Model Rubric
## Revenue Projections
- Uses historical revenue data from the last 5 fiscal years