> ## Documentation Index > Fetch the complete documentation index at: https://docs.galileo.ai/llms.txt > Use this file to discover all available pages before exploring further. # Custom Decision Model Metrics > Learn when and how to use decision model metrics Custom decision model metrics classify and score text records. Each metric asks one question and returns a typed answer with probabilities, without a written explanation. This guide describes when and how to use decision model metrics. ## Supported decision models Galileo supports the following decision model: | Decision model | Provider | Setup | | - | - | - | | Jev | TypeSafe | Set up a [decision model integration](https://docs.galileo.ai/sdk-api/third-party-integrations/decision-models/decision-models.md). | ## How decision model metrics work A decision model is not an LLM. You provide a record, a plain-language question, and the allowed answers. The model returns an answer with probabilities and does not provide a written explanation. The following table describes the supported question types and results: | Question type | Metric output type | Result | | - | - | - | | True/False | Boolean | Returns `true` when the probability is at least 0.5; otherwise returns `false`. | | Choice | Categorical | Selects one of the categories you define. | | Score | Discrete | Selects the most likely level from your rubric. | ## When to use a decision model metric Decision model metrics classify and score large volumes of text faster and at a much lower cost than LLM-as-a-judge metrics. For example, you can use decision model metrics to monitor high-volume Log streams at full coverage and perform classification-style checks for frustration, task completion, tone, and policy adherence. Use an [LLM-as-a-judge metric](https://docs.galileo.ai/concepts/metrics/custom-metrics/custom-metrics-ui-llm.md) when you need explanations, counts or percentages, images, audio or files, or very long inputs. For more information on metric differences, see [Which metric should I use?](https://docs.galileo.ai/concepts/metrics/overview.md#which-metric-should-i-use) ## Create and use decision model metrics ### Create a decision model metric Before you begin, [set up a decision model integration](https://docs.galileo.ai/sdk-api/third-party-integrations/decision-models/decision-models.md). **1. Navigate to the Metrics page** From the Galileo main menu, select **Metrics**. **2. Configure the metric** Select **Create metric**. Follow the on-screen instructions to configure the metric. If your experiment needs an expected answer, turn on **Use ground truth**. For guidance on writing questions, see [How to write effective questions](#how-to-write-effective-questions). **3. Test the metric** Select **Test metric** to test the metric. You can test with manual input, current logs, or a dataset. Dataset testing scores **Macro F1** for boolean and categorical, and **RMSE** for discrete. See [Test Metrics](https://docs.galileo.ai/concepts/metrics/custom-metrics/test-metrics.md) for more information. Update the metric as needed, then select **Create Metric**. After you create a metric, editing and saving it again creates a new metric version. You can't change **Apply to** or **Output type** after creation. To change either setting, duplicate the metric and configure the copy. ### Decision model metric batching When decision model metrics use the same model and inputs, Galileo batches up to 10 metrics in a single call to reduce cost. Each metric still receives its own answer. If one metric in the batch fails, all metrics in the batch fail and show a clear error. Hover over a metric value to see how many metrics were included in the batch. The cost shown for each metric is an estimate calculated as a fraction of the total batch cost based on the batch size. ### How to write effective questions Ask one question per metric. If a rubric checks several qualities, split it into separate metrics. Follow these guidelines based on your question type: * For a question with multiple applicable labels, create one boolean metric per label. * For a categorical question, consider creating an **Unclear** category. The model always selects an answer, even when the record doesn't clearly fit the other categories. * For a discrete question, describe each level in concrete terms so adjacent levels are distinguishable. Example questions include: * “Was the user frustrated?” * “Did the agent complete the task?” * “Did the response follow the stated policy?” Test questions against examples you have labeled yourself before relying on their results. ### Use decision model metrics Decision model metrics work in [Log streams](https://docs.galileo.ai/concepts/logging/configure-metrics/configure-metrics.md), [experiments](https://docs.galileo.ai/sdk-api/experiments/experiments.md), and playgrounds, at every step level. To enable one, select **Configure Metrics** within one of those pages and turn on a metric marked with the **Decision** type. [Composite metrics](https://docs.galileo.ai/concepts/metrics/custom-metrics/composite-metrics.md) can use decision model results. For a boolean decision model metric, the composite receives its probability. Charts, filters, alerts, and roll-ups work as they do for other metrics with the same output type. ### Read decision model metric results A decision model result appears like any other metric result with the same output type. Hover over a result to see its confidence, answer probabilities, model version, token usage, and estimated cost. Each result has one of four states: **Success**, **N/A**, **Error**, or **Pending**. ## Limits and troubleshooting Decision models accept text only. A record containing images, audio, or documents shows **N/A**. The record and question must fit within a 32k-token context window. Galileo does not trim oversized input. If a shared call fails, every metric in that call shows the error. The following table describes common errors and how to troubleshoot them: | **What you see** | **What to do** | | - | - | | Authentication error | As the run creator, add or replace your decision model API key. | | Rate-limit error | Raise your decision model quota or use sampling. | | Input exceeds the provider's context window | Change **Input style** to **I/O only**. | | **N/A: Unsupported file types** | Use an [LLM-as-a-judge metric](https://docs.galileo.ai/concepts/metrics/custom-metrics/custom-metrics-ui-llm.md) for multimodal records. | | **N/A: Ground truth required** | Add the expected output to the dataset. | | **N/A: Sampled out** or **Filtered out** | No action is needed. | | Model is no longer available | Move the metric to a replacement model version. | | Toggle disabled in **Configure Metrics** | Add a [decision model integration](https://docs.galileo.ai/sdk-api/third-party-integrations/decision-models/decision-models.md) for the run creator. | See [Decision Models](https://docs.galileo.ai/sdk-api/third-party-integrations/decision-models/decision-models.md) for more information on the decision model integration, including billing and rate limits.