Repeatability
High
REST API spec documents follow well-established structural conventions — endpoints, request/response schemas, auth flows, error codes, versioning. The task is highly templatable and AI has seen thousands of examples in training data.
Ambiguity Tolerance
Medium
The domain areas (auth, catalog, orders) are named but the specific business rules, data models, and non-functional requirements are unspecified. A competent draft is achievable, but 'done' is hard to define without knowing what the actual system needs to do.
Data & Tool Availability
Medium
No external tools or live data access are required — this is a pure writing task. However, the agent lacks access to existing codebases, internal data models, or stakeholder decisions that would make the spec accurate rather than generic.
Error Cost
Low
The output is a draft document with no direct system impact. Errors are caught in human review before any implementation begins, making this a low-stakes, fully reversible task.
Human Judgment Required
Medium
Architectural decisions — auth strategy, pagination design, versioning policy, rate limiting — reflect real tradeoffs that depend on team expertise, scale expectations, and existing infrastructure. A human engineer must validate these choices even if AI drafts them competently.