---
title: Agent Designer
description: >-
  Use Describe With AI to create production-ready Agents from a natural language
  description.
ogTitle: Agent Designer Guide
ogDescription: >-
  Create controlled Agents from natural language descriptions, including
  variables, steps, loops, tools, validation, and benchmarks.
ogImage: /assets/images/og/agents-designer.webp
navigation:
  icon: fasl fa-comment
---

# Agent Designer

Agent Designer, also called **Describe With AI**, creates a complete Agent from a natural language description. Instead of manually configuring every step, variable, loop, and output, you describe the work the Agent should perform and the designer drafts the Agent for review.

## How It Works

Designer uses a two-phase flow.

### Phase 1: Clarifying Questions

After you describe the Agent, the designer may ask clarifying questions about inputs, outputs, sources, tools, schedules, or review requirements.

Questions may be multiple choice or open-ended. Answer them and send the responses to continue. If your initial description is detailed enough, the designer may proceed directly to generation.

### Phase 2: Agent Generation

The designer drafts the Agent, including:

- Agent variables
- prompt steps
- loop steps for collections
- JSON validation or structured output settings
- model and reasoning assignments
- source connection expectations
- tool usage where appropriate
- benchmark configuration
- final output selection

The generated Agent is a starting point. Review it before running it on sensitive content or scheduling recurring execution.

## Write Effective Descriptions

Describe three things clearly: inputs, outputs, and processing.

Good input examples:

- "Input: an uploaded contract PDF."
- "Inputs: company name, reporting period, and selected Site."
- "Input: a JSON array of customer names."
- "Read approved policy folders from the selected Site."

Good output examples:

- "Output a markdown report with executive summary, findings, risks, and recommended actions."
- "Extract key terms as JSON with effective date, term length, renewal, liability cap, and termination rights."
- "Create a spreadsheet with one row per counterparty and columns for risk level, clause reference, and suggested follow-up."

Good processing examples:

- "For each contract, extract terms, validate the JSON, then summarize risks."
- "Use Site content only; do not use web search."
- "Use web search only for current public market data, then cite approved Site documents separately."
- "Generate a PowerPoint deck after the analysis is complete."

## What the Designer Builds

The designer applies Agent design patterns such as:

- isolated steps with explicit context
- variable wiring
- structured outputs
- loop handling for lists
- validation steps
- tool calls where allowed
- benchmark setup

When imported, the Agent opens in the editor so you can adjust prompts, variables, connections, and policy before running.

## Review Before Production

Before scheduling or sharing outputs, review:

- selected model and reasoning effort
- permitted source connections
- controlled tools and egress settings
- generated file settings
- benchmark and review gates
- output template
- evidence requirements

See [Agent Connections](/agents/connections), [Controlled Tools and Egress](/agents/controlled-tools-and-egress), and [Benchmarks](/agents/benchmarks).