Decomposition changes the scoring, not just the wording. If the grader aggregates boolean answers into an accuracy score [3], every question carries equal weight unless you say otherwise. Take a ten-question rubric: each check is worth 10 percent. Split one compound question in two, which is exactly what the post prescribes for "Does the response contain a metadata property and format the output as JSON?" [7], and you now have eleven questions, and that single requirement carries 2/11, about 18 percent [16]. The rule against overlapping questions [8] is the same arithmetic from the other end: two questions about one concept double the penalty for one mistake. Question authoring is weight authoring. Nobody writes those weights down, which is why they drift.
The rest of the guidance is a testability filter. Intent, quality and reasoning are out, because they require interpretation rather than observation [9]. The recommended vocabulary is RFC 2119: MUST, MUST NOT, REQUIRED [10]. Those are all obligations, and that is the point, since a requirement you would merely prefer has no TRUE or FALSE. The best line in the post is the one about negative constraints: instead of asking whether the agent used best practices, check that it did not suggest a specific deprecated feature [11]. "Followed best practices" is not decidable by any grader. "Did not recommend feature X" is.
The cost claim rides on that filter. The team argues a smaller, faster model suffices because strict boolean evaluation is a less complex task [6]. For that to transfer to your harness, each question has to be answerable from the response text alone, with no environment access and no domain knowledge the small model lacks. A deprecation check qualifies only if the rubric names the feature; leave it implicit and the cheap grader is guessing about your API surface.
What the material does not contain is a measurement. The reduction in rating variance is asserted as practice [12][17], with no agreement figures between graders or between runs. That is the number I would want before swapping in a smaller judge, and it is cheap to produce: run the same responses twice and count disagreements per question. The other half of the risk is coverage, and the post is direct about it. Grading requirements the prompt never stated manufactures false negatives [14], so a rubric misaligned with the task measures the rubric.
One structural consequence is easy to miss. The advice to keep scoring rubrics in a separate system exists because agents tailor answers to whatever tests they can see [13], and these skills are published on GitHub [1]. Public artifact, private assertions. If the rubric ever lands next to the skill file, the score stops being evidence.
