Set a quality and verification bar

For make a multi-constraint laptop recommendation auditable without requesting hidden reasoning, define quality across accuracy, completeness, usefulness, safety, and reproducibility. Weight dimensions according to harm. A cosmetic miss can be revised; an unsupported claim, broken calculation, privacy leak, or rights violation blocks release.

Translate each dimension into observable checks. Accuracy means a claim, value, behavior, or frame agrees with an authoritative source. Completeness means every required field or stage appears. Usefulness means a college buyer who must verify seller claims can take the intended action. Safety includes the boundary that you must do not include account details, private purchase history, or personally sensitive constraints unless they are necessary and safe to share. Reproducibility means the prompt, input version, settings, and review evidence are saved.

Use checks from cheapest to strongest:

1. Contract check: required sections, schema, length, and prohibited content.
2. Source check: trace claims and values to supplied evidence.
3. Edge check: run normal, boundary, missing, and adversarial cases.
4. Independent check: calculate, test, rehearse, listen, inspect, or open the original.
5. Human gate: a responsible reviewer approves consequential use.

In this chapter, the concrete verification is to open authoritative product pages, recalculate weighted scores, check units and model variants, test software requirements, and see whether the recommendation changes under reasonable weights. The expected candidate is A criteria table, explicit unknowns, a short recommendation tied to three inspectable facts, and a verification checklist. Record actual evidence, not a checkbox copied from the prompt.

Score each criterion 0 (fails), 1 (partly), or 2 (passes). Any zero for factual correctness, permission, privacy, or required disclosure is an automatic stop. A total score is useful for comparing iterations, but it must never average away a blocking defect.

Compare three laptops for college using price, measured battery life, weight, and required-software compatibility. First output a short comparison plan and evidence table. Then recommend one in under 150 words with three deciding facts. Finally list unknowns to verify on seller pages. Give concise rationale, not private hidden reasoning.

After generation, sample beyond the happy path. Failures such as equating longer rationale with truth; post-hoc justification; invented specifications; hidden weighting; arithmetic that cannot be reproduced often survive a superficial review because the output has the right shape. Use a counterexample designed to expose the riskiest assumption.

Store the rubric result, reviewer, date, input version, failed cases, and unresolved limitations. If the artifact changes, rerun affected checks. Ask for visible work products—plans, formulas, evidence tables, assumptions, and checks. A model's private reasoning is neither required nor a substitute for proof. Quality assurance is part of the work, not an apology added at the end.