The Regression Tax: Decomposing Why Skills Help and Hurt LLM Agents
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TL;DR - A nearly 6,000-run study shows procedural skills can reduce LLM-agent reliability by introducing regressions. Better grounding and output verification matter more than procedural guidance alone.
- Stronger skills primarily succeed by causing fewer regressions, not by producing more gains.
- Regressions arise through description osmosis, grounding displacement, and verification displacement.
- Existing skills overemphasize procedures while undersupporting grounding and verification, the leading sources of persistent errors.
- Skill evaluations should report gains and regressions separately rather than only aggregate success improvements.
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The Regression Tax: Decomposing Why Skills Help and Hurt LLM Agents
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TL;DR - A nearly 6,000-run study shows procedural skills can reduce LLM-agent reliability by introducing regressions. Better grounding and output verification matter more than procedural guidance alone.
- Stronger skills primarily succeed by causing fewer regressions, not by producing more gains.
- Regressions arise through description osmosis, grounding displacement, and verification displacement.
- Existing skills overemphasize procedures while undersupporting grounding and verification, the leading sources of persistent errors.
- Skill evaluations should report gains and regressions separately rather than only aggregate success improvements.