Repeatability
High
The transformation rules are structurally consistent: column mapping, salary parsing, and deduplication follow the same logic every run. If the sheet structure changes, the agent needs updating, but for this one-time or periodic job the pattern is stable.
Ambiguity Tolerance
Medium
Most success criteria are crisp—standardized columns, numeric salary fields, dedup flags—but edge cases like near-duplicate candidates (same name, different email) or ambiguous salary strings ('competitive') require a defined rule or human call. These are solvable with upfront spec but not zero-ambiguity.
Data & Tool Availability
High
Google Sheets has a well-supported API and the agent can read all five sheets directly. No external data sources or special permissions beyond sheet access are needed, making this straightforward to wire up.
Error Cost
Low
The source sheets are preserved, so any mistake in the output is fully reversible—just rerun the transformation. The worst realistic outcome is a missed duplicate or a mis-parsed salary range, both catchable in a quick human review.
Human Judgment Required
Low
Column renaming and salary parsing are rule-based, not taste-based. Deduplication by name/email/phone is algorithmic. The only genuine judgment call is resolving ambiguous near-duplicates, which can be flagged for human review rather than decided by the agent.