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Benchmark finds Claude models already avoid most data-analysis traps a custom agent skill targets

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The author built a custom agent skill to improve coding agents at data analysis and tested it against 30 realistic cases, each containing one planted trap with a code-verified correct answer. The cases covered 19 data-analysis pitfalls and 8 performance or reliability pitfalls, plus 3 tasks where the agent measures its own work. Each case was run with and without the skill on Claude Haiku 5.5 and Sonnet 5.5 and graded by an LLM judge. Both models scored near perfectly even without the skill, with the largest gain coming from Haiku's score rising from 58/61 to 61/61. The author concluded that skills help most where a model's knowledge is weakest and that a skill must activate to be useful.

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