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…LLMs already "know" these books deeply, but without a structured prompt scaffold they apply that knowledge inconsistently and at low confidence. Giving the model a explicit lens — "review this as if you're checking against Clean Code heuristics C1–C36" — concentrates attention and dramatically reduces hallucinated or off-topic feedback…
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Where I'd push back or warn you:
Context collapse is your #1 enemy. Clean Code was written for Java in 2008. DDIA is about distributed systems at scale. If you apply the Clean Code reviewer to a 50-line Python script, you'll get pedantic nonsense about function length when the actual problem might be that the data model is wrong. Your skill selection logic needs to be domain-aware, not just "throw all skills at every file"…
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