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A Reading step uses a language model to evaluate the results of a DQL query, which may return transcripts, metadata, prior Reading results, or text. Reading steps are most helpful for operations like classifying transcripts, extracting structured information, or synthesizing results across runs. Your coding agent generates Reading steps inside Analysis Plans that you may approve in the UI. To skip approval, instruct your coding agent to “auto approve all reading steps.”

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Inputs

Every Reading step is paired with a DQL query that selects its inputs. The DQL query determines which runs (or which prior results) the Reading step sees and how they’re grouped, giving you precise control over what it evaluates. Each parameter in a Reading step’s prompt template has a type that determines what data it carries:
TypeDescription
transcriptA full transcript and transcript-level metadata
transcript_sliceA contiguous portion of a transcript, e.g., the last N turns.
agent_runAll transcripts in an AgentRun and run-level metadata
reading_resultThe output of a prior Reading step.
textA string derived from a metadata field or DQL expression.
Any parameter can be a list selected with ARRAY_AGG. This is useful when the number of desired inputs varies row to row.

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Output schema

The output schema is a JSON Schema object that constrains the judge’s response. Standard types (string, number, boolean) and enum values are supported. Set "citations": true on a string field to have the judge ground its output in specific passages from the input. The coding agent proposes a schema based on your question; you can ask it to add, remove, or rename fields. 
{
  "type": "object",
  "properties": {
    "summary": {
      "type": "string",
      "citations": true
    }
  },
  "required": ["summary"]
}

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Reading steps in the plan UI

When your coding agent generates an Analysis Plan, each Reading step appears in the UI with four sections:
  1. Summary. A one-line description of what the step does, with the step’s alias (e.g., $2) and the step it reads from (e.g., “Data from $1”). Other steps reference this step’s output by alias.
  2. Prompt template. The full prompt the judge receives for each input row. Parameters appear as labeled pills. When the step is run, the parameters are filled from the input data.
  3. Output schema. The JSON Schema that constrains the judge’s response. In order to view the output schema, click on the Output Schema pill in the UI.
  4. Results. A table of the judge’s output, displaying one result row per input. You can toggle between Compact and Detailed view to see more of the output inline. Clicking on a result will open it in the sidebar, and you can use the up and down arrow keys to review different result rows.
A Reading step in the plan UI: summary header with step ID and data source, prompt template, output schema, and a results table.