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What marks a set-up trace as useful for training?

A checklist of traits that separate a useful set-up training trace from a thin one, focused on conditions, exceptions, handovers and verifiable end state.

A useful set-up trace shows decisions and consequences, not only the final record. Look for these traits when reviewing a sample:

- **A source decision** with explicit conditions, an approver role and an effective date. - **Ambiguity to resolve**, such as two near-matching party records or a partly complete application. - **A policy that constrains action**, for example a rule about which product tier applies or when activation is allowed. - **At least one rejection or exception** from the target system, with the response the worker chose. - **A handover** that names the receiving team and carries the information they need. - **A checkable end state** where every created or changed record can be compared with policy. - **Consistent identifiers** so a party, account, case and task link to each other without gaps. - **Timestamps in a plausible order**, so waiting periods and reopened tasks make sense.

Traces missing most of these tend to teach only the happy path. Because the material is generated, also ask how each trait was grounded and check the sample for disclosure risk.

Use these traits to screen any set-up dataset quickly, including ones from other sources, before committing evaluation or training effort.

Audience:
Model labs
Content type:
Checklist
Buyer question:
What it is and why it matters

Content release: r-a220eb6e099b243b

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