Agent Step Prompts

Last Updated: June 12, 2026

Agent step prompts for Workflow are natural language instructions that help you analyze data and generate or rewrite content based on data from previous workflow steps. Agent steps are restricted to generating text output only. Keep this restriction in mind when writing prompts to optimize output and ensure workflow continuation.

This feature is in beta. Capabilities, configuration, and availability might change as development continues. Contact your Vasion representative with feedback to help shape this feature.

Operation Prompts

The Agent step interprets natural language to analyze data and generate text output. The following prompts and examples demonstrate different approaches based on your needs.

Analysis Prompts

Use these prompts to analyze data from previous workflow steps.

Simple Analysis

Review <data source>, and identify <what to look for>.

The following are examples:

  • Review this invoice, and flag any line items that exceed $5,000.
  • Check this document for missing required fields, and list what is absent.
  • Analyze this claim, and list any common denial triggers.
Scored Assessment

Evaluate <data source> against <criteria>, and provide a <score or rating> with reasoning.

The following are examples:

  • Evaluate this contract against our standard terms checklist, and provide a completeness score from 1 to 10 with a list of missing clauses.
  • Assess this support request for high, medium, or low urgency, and explain your reasoning.
  • Review this app for completeness, and rate each section as complete, partial, or missing.

Generation Prompts

Use these prompts to produce new content based on workflow data.

Text Generation

Using <data from previous steps>, generate <output>.

The following are examples:

  • Using the patient data and diagnosis codes from the previous steps, generate a letter of medical necessity for prior authorization.
  • Using this form submission, draft a personalized acknowledgment email with the submitter's name and expected timeline.
  • Using these extracted invoice fields, generate a summary suitable for the approver.
Rewriting and Formatting

Rewrite <input> to meet <standard or format>.

The following are examples:

  • Rewrite these free-text notes into standardized language that meets our compliance formatting requirements.
  • Reformat this extracted data into a clean summary with these labeled fields: Name, Date, Amount, and Status.

Prompt Approaches

Choose your prompting approach based on how well-defined the task is and the output you need.

Direct Instruction

Use clear, specific prompts when you know exactly which output you need. This approach works best for well-defined tasks.

You can do the following:

  • Tell the agent exactly what to look for and how to format the output.
  • Specify the structure, such as "Respond with: <field 1>, <field 2>, <field 3>."
  • Include the criteria or rules the agent should apply.

Contextual Analysis

Use open-ended prompts when you want the agent to interpret and reason about the data. This approach works best for review and assessment tasks.

You can do the following:

  • Let the agent identify issues, patterns, or anomalies.
  • Ask for reasoning alongside conclusions.
  • Refine with follow-up instructions in subsequent Agent steps.

Recommendations

Follow these recommendations to get the best results from the Agent step:

  • Define the output structure: Because the agent outputs text, tell it how to format the response. This approach makes the output predictable and useful.
  • Reference previous step data explicitly: Mention which data is coming from the prior step so that the agent knows which inputs to expect.
  • Keep instructions focused on one task: One Agent step should do one cognitive job. Chain multiple Agent steps for multistage analysis rather than combining everything into one prompt.
  • Test with real workflow data: Prompt quality depends on the data in the workflow. Test with actual documents and form submissions.
  • Send output to email: To deliver agent output to a user, add an Email step after the Agent step, and include the agent output variable in the email body. For more details refer to Email Step.

Next Steps

Refer to the following: