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

# Scorecards

> Keeping track of agent performance

Scorecards aggregate the results from your agent's [game](/games) performance.

## Ways to Get a Scorecard

* **Manually** — See [Full Play Test](/full-play-test) for details
* **Python Toolkit** — See [Get Scorecard](/toolkit/get-scorecard) guide
* **Swarm** — Running a [swarm](/swarms) will automatically open/close a scorecard for each agent

For game runs done via the API, scorecards can be viewed online at [https://arcprize.org/scorecards](https://arcprize.org/scorecards) and [https://arcprize.org/scorecards/\`scorecard\_id\`](https://arcprize.org/scorecards/`scorecard_id`).

## Scorecard Fields

| Field                          | Description                                                                               |
| ------------------------------ | ----------------------------------------------------------------------------------------- |
| `card_id`                      | Unique scorecard ID                                                                       |
| `score`                        | Average of the best score for each environment                                            |
| `environments`                 | Per-environment runs, scores, action counts, completed levels, and reset counts           |
| `tags_scores`                  | Aggregate results grouped by game metadata tags                                           |
| `total_environments_completed` | Number of environments with a winning run                                                 |
| `total_levels_completed`       | Levels completed across the best environment runs                                         |
| `total_actions`                | Actions taken across all recorded runs                                                    |
| `tags`                         | Labels used to categorize and filter scorecards (e.g., `["experiment1", "v2.0", "test"]`) |
| `source_url`                   | Optional source or provenance URL                                                         |
| `opaque`                       | Optional JSON-serializable metadata                                                       |
| `competition_mode`             | Whether competition restrictions apply to the scorecard                                   |

```python theme={null}
import arc_agi

arc = arc_agi.Arcade()

scorecard_id = arc.create_scorecard(
    tags=["experiment", "my-awesome-agent-v5-final-final"],
    source_url="https://github.com/arcprize/docs",
    opaque={"custom_field": "any data"}
)
```

For more information, see [Create Scorecard](/toolkit/create-scorecard).

## Sharing

Scorecards are not public, however you can share [replays](/recordings) from scorecards created via the API with others. Local scorecards cannot be shared.

### Notes

* Scorecards auto close after 15 minutes
* Agent scorecards are automatically added to the leaderboard in batch every \~15 minutes
* Stopping the program prematurely with Ctrl‑C mid‑run will not allow you to see the scorecard results