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

# List Eval Agent Templates

> List the read-only library of shipped eval agent templates.

### Headers

<ParamField header="authorization" type="string" required>
  Your API key for authentication.
</ParamField>

### Response

<ResponseField name="object" type="string">
  Always `list`.
</ResponseField>

<ResponseField name="data" type="array">
  Array of eval agent template objects.

  <Expandable title="template object">
    <ResponseField name="key" type="string">
      Unique identifier key for the template, for example `hallucination_detection`.
    </ResponseField>

    <ResponseField name="name" type="string">
      Human-readable display name.
    </ResponseField>

    <ResponseField name="description" type="string">
      Brief description of what the template evaluates.
    </ResponseField>

    <ResponseField name="category" type="string">
      Template category. One of `voice`, `sales`, `support`, `scheduling`, `compliance`, or `quality`.
    </ResponseField>

    <ResponseField name="modality" type="string">
      Evaluation modality. Either `text` or `audio`.
    </ResponseField>

    <ResponseField name="system_prompt_md" type="string">
      The system prompt used for this eval agent, in Markdown.
    </ResponseField>

    <ResponseField name="prompt_md" type="string">
      The evaluation prompt, in Markdown.
    </ResponseField>

    <ResponseField name="levels" type="array">
      Ordered scoring levels for this template.

      <Expandable title="level object">
        <ResponseField name="level_key" type="string">
          Short identifier for the level, 1-64 characters.
        </ResponseField>

        <ResponseField name="label" type="string">
          Display label for the level, 1-80 characters.
        </ResponseField>

        <ResponseField name="prompt_md" type="string">
          Prompt describing this level's criteria, in Markdown.
        </ResponseField>

        <ResponseField name="color" type="string">
          Optional display color. One of `rose`, `amber`, `gold`, `emerald`, `blue`, `indigo`, `violet`, or `fog`.
        </ResponseField>
      </Expandable>
    </ResponseField>

    <ResponseField name="target_level_keys" type="array">
      Array of `level_key` strings that represent the passing threshold for this template.
    </ResponseField>
  </Expandable>
</ResponseField>

<ResponseField name="has_more" type="boolean">
  Always `false`. This endpoint returns the full library in a single page.
</ResponseField>

<ResponseField name="next_cursor" type="string">
  Always `null` for this endpoint.
</ResponseField>

<ResponseExample>
  ```json Response theme={null}
  {
    "data": {
      "object": "list",
      "data": [
        {
          "key": "hallucination_detection",
          "name": "Hallucination Detection",
          "description": "Detects factual inaccuracies or fabricated information in agent responses.",
          "category": "quality",
          "modality": "text",
          "system_prompt_md": "You are an expert evaluator assessing whether an AI agent fabricated information.",
          "prompt_md": "Review the conversation and determine whether the agent stated anything that was factually incorrect or unsupported.",
          "levels": [
            {
              "level_key": "no_hallucination",
              "label": "No Hallucination",
              "prompt_md": "The agent made no factually incorrect or unsupported claims.",
              "color": "emerald"
            },
            {
              "level_key": "minor_hallucination",
              "label": "Minor Hallucination",
              "prompt_md": "The agent made one or more small inaccuracies that did not materially mislead the user.",
              "color": "amber"
            }
          ],
          "target_level_keys": ["no_hallucination"]
        },
        {
          "key": "call_resolution",
          "name": "Call Resolution",
          "description": "Assesses whether the agent successfully resolved the caller's issue.",
          "category": "support",
          "modality": "audio",
          "system_prompt_md": "You are an expert evaluator assessing call resolution quality.",
          "prompt_md": "Did the agent fully resolve the caller's stated issue before ending the call?",
          "levels": [
            {
              "level_key": "resolved",
              "label": "Resolved",
              "prompt_md": "The caller's issue was fully addressed.",
              "color": "emerald"
            },
            {
              "level_key": "unresolved",
              "label": "Unresolved",
              "prompt_md": "The caller's issue was not addressed or was left open.",
              "color": "rose"
            }
          ],
          "target_level_keys": ["resolved"]
        }
      ],
      "has_more": false,
      "next_cursor": null
    },
    "errors": null
  }
  ```
</ResponseExample>

***

Docs for agents: [llms.txt](/llms.txt)