> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Accuracy

> Accuracy examples evaluate how well responses match expected outputs.

| Example                                                                                 | Description                                                                              |
| --------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------- |
| [Basic Accuracy Evaluation](/examples/evals/accuracy/accuracy-basic)                    | Demonstrates synchronous and asynchronous accuracy evaluations.                          |
| [Comparison Accuracy Evaluation](/examples/evals/accuracy/accuracy-9-11-bigger-or-9-99) | Demonstrates accuracy evaluation for numeric comparison tasks.                           |
| [Team Accuracy Evaluation](/examples/evals/accuracy/accuracy-team)                      | Demonstrates evaluating language routing accuracy for a team.                            |
| [Given Answer Accuracy Evaluation](/examples/evals/accuracy/accuracy-with-given-answer) | Demonstrates accuracy evaluation for a provided answer string.                           |
| [Tool-Enabled Accuracy Evaluation](/examples/evals/accuracy/accuracy-with-tools)        | Demonstrates accuracy evaluation for an agent using calculator tools.                    |
| [Db Logging](/examples/evals/accuracy/db-logging)                                       | Demonstrates storing accuracy evaluation results in PostgreSQL.                          |
| [Evaluator Agent](/examples/evals/accuracy/evaluator-agent)                             | Demonstrates accuracy evaluation using a custom evaluator agent.                         |
| [Accuracy Eval Metrics](/examples/evals/accuracy/accuracy-eval-metrics)                 | Accumulate eval model metrics into the agent's run output alongside agent model metrics. |