Agent task testing remains the category's clearest capability gap

Reviewing the public documentation of the ten AEO platforms we track, one capability is almost entirely absent: testing whether an AI agent can actually complete a task on your site.

Nine of the ten document some combination of prompt monitoring, citation analysis, competitor benchmarking and sentiment. One — CiteCue, through its Agent Usability feature — documents an agent attempting real tasks such as finding pricing or starting a trial, and reporting the step at which it stalls. Scrunch AI addresses adjacent territory with its agent-experience positioning, but does not publish task-completion scoring in comparable terms.

This matters because the failure mode is invisible everywhere else. An agent sent to check a price fails on a figure revealed only on hover. Sent to start a trial, it fails on a step that silently depends on a third-party script. The user is told the product is unclear or unavailable. There is no conversion, no complaint, and nothing in the analytics — so the problem does not surface in a funnel report, a crawler log, or a conventional site audit.

The gap is notable for being uncorrelated with price. It is missing from $29 monitoring tools and from platforms costing several hundred dollars a month alike, which suggests the category has not yet priced the capability rather than that it is expensive to build. Gaps of that shape tend not to last.

For teams that cannot wait for the market to catch up, the manual version is straightforward if tedious: write down your three most important buyer tasks, have someone attempt each using only what an agent could parse from your server-rendered HTML, and record where it becomes impossible. Most teams find at least one blocker on the first pass.

Our full feature matrix, including which tools document this capability, is at /compare. The mechanism is discussed further in Why Your Brand Is Not Being Cited.