REA documents a path from a retained web network capture to an agent environment for evaluation or reinforcement learning. The exported environment answers from recorded evidence and can model confirmed state changes; it does not reproduce every behavior of the original application. Review capture coverage, generated tools and framework requirements before calling a task representative.
What the recording supports
A capture retains only requests and responses actually observed. REA projects them into a manifest and runnable bundle. An action without retained evidence may remain unsupported. Running a bundle also has AgentEnv and Docker requirements beyond offline export.
Evaluate fidelity
Design tasks covered by the capture and check both successful and unsupported actions. Compare a narrow probe with the authorized live app when feasible. A passing smoke task proves one bundle and framework setup, not general app fidelity. Review sensitive capture data before sharing.
Requirements & evidence
- Resource type
- Guide
- Category
- Unknown
- Host platforms
- Unknown
- Targets
- web
- Level
- Advanced
- Source checked
- 2026-11-03T11:05:20.225303+00:00
Primary sources
Source descriptions establish documented scope. They do not establish that every workflow has been reproduced by AI Craft Pad.