What is a cyclic agent workflow?

A cyclic agent workflow is a workflow that can return to an earlier step and repeat part of its execution until a defined condition is met. In a graph, this is represented by a loop-back edge. Cycles are useful when an agent must inspect a result, improve it, and check again rather than assume the first attempt is correct.

Example: Generating API tests

An agent needs to create tests for a payment API endpoint:

1. Generate tests from the endpoint requirements.
2. Validate coverage, assertions, and output format.
3. Inspect the result.

• If all mandatory checks pass, publish the test suite.
• If a fixable gap remains and attempts are available, revise the affected tests.
• If the retry limit is reached or a safe fix is impossible, stop and report the issue.

1. After revision, return to Validate.

The recurring path is:

Generate → Validate → Revise → Validate → ... → Exit

For example, the first validation may reveal that the generated tests omit the 401 Unauthorized case. The agent adds that test and validates again. If coverage now passes, the loop ends.

How is this different from a sequential workflow?

A sequential workflow follows a chain of steps without returning to an earlier step.

A cyclic workflow allows execution to revisit a node based on current state. The loop is conditional: the workflow should exit once its goal is satisfied or a defined stopping rule is triggered.

When are cycles useful?

• Generate–critique–revise: Improve an answer, plan, or artifact when an objective check identifies a gap.
• Tool-result correction: Retry a recoverable operation after adjusting invalid inputs.
• Iterative investigation: Gather additional evidence when a specific required fact is still missing.
• Incremental task processing: Handle remaining work items one at a time until the queue is complete.

Cycles should have a clear purpose. Repeating the same prompt without new information or a useful correction can increase latency and cost without improving quality.

What prevents an infinite loop?

A robust cyclic workflow needs:

• Exit conditions: Explicit success, non-recoverable failure, and cancellation outcomes.
• Iteration limits: A maximum number of attempts or revisions.
• Resource limits: Time, token, tool-call, and cost budgets.
• Progress checks: Detect unchanged outputs or repeated errors.
• Persisted state: Track iteration count, last validation result, and why a retry was chosen.
• Safe retries: Check whether an external action already succeeded before repeating it.

For example, three validation attempts may be a configured limit, but the correct threshold depends on the task's risk, cost, and recovery strategy.

In short

Cyclic agent workflows support controlled iteration. They let agents revisit earlier steps to improve or recover results while explicit stopping conditions prevent endless execution.