Repeatability
High
Data cleaning and ETL pipelines are structurally identical across runs — parse, validate, deduplicate, normalize, serialize. The rules here (ISO 8601 timestamps, session-ID deduplication, JSON output) are deterministic once edge cases are defined.
Ambiguity Tolerance
Medium
Most success criteria are crisp (ISO 8601, deduplicated session IDs, valid JSON), but the deduplication strategy when session IDs conflict across UUID vs. numeric user IDs is underspecified, and the exact JSON schema for the BI tool is not provided — both require a quick clarification before the agent can proceed confidently.
Data & Tool Availability
High
The user has the CSV export ready and the output format is a standard JSON structure. A code agent needs only the file, a Python or pandas environment, and the target JSON schema — no external APIs or live credentials required.
Error Cost
Medium
A bad deduplication or timestamp conversion silently corrupts downstream BI analysis, which could mislead business decisions. However, the original CSV is preserved, so errors are reversible — the cost is wasted time and a re-run, not permanent data loss.
Human Judgment Required
Low
There are no taste, ethics, or relationship calls here. The few judgment points — how to handle null critical columns, which timestamp wins in a conflict — can be resolved with explicit rules the user provides upfront or the agent surfaces as questions before writing code.