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Copy file name to clipboardExpand all lines: docs/explorer/benchmarks.md
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### Step 3: Associate Your Agent Dataset with a Benchmark and Score
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[Instructions on updating](./Explorer_API/Dataset_Metadata/update_dataset_metadata_api.html) the datasets's metadata to include the `benchmark`, `name` and `accuracy` fields, that will associate your agent dataset with a specific benchmark and score.
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[Instructions on updating the datasets's metadata](./Explorer_API/Dataset_Metadata/update_dataset_metadata_api.md) to include the `benchmark`, `name` and `accuracy` fields, that will associate your agent dataset with a specific benchmark and score.
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For instance, to associate your `gpt-4o` agent dataset with the `webarena` benchmark and an accuracy score of `0.5`, you can update the dataset's metadata as follows:
Copy file name to clipboardExpand all lines: docs/explorer/index.md
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You can use Explorer to visualize, analyze, and collaborate on your AI agent traces, as well as compare them with other agents and models.
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<center>Viewing agent traces in Explorer</center>
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## 1. Create an Explorer Account
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First, navigate to the <imgclass='inline-invariant'src="assets/logo.svg"/> [Invariant Explorer](https://explorer.invariantlabs.ai) and create an account via GitHub Sign-In.
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<divclass='tiles'>
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<ahref="benchmarks.html"class='tile'>
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<ahref="benchmarks"class='tile'>
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<span class='tile-title'>Benchmarks →</span>
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<span class='tile-description'>Submit your AI agent to the Invariant benchmark registry for comparison</span>
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</a>
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<ahref="Explorer_API/2_traces.html"class='tile'>
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<ahref="Explorer_API/2_traces"class='tile'>
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<span class='tile-title'>Trace Format →</span>
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<span class='tile-description'>Learn about the Invariant trace format and how to structure your traces for ingestion</span>
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