Code-Execution Decision — emit-code-vs-reason

One-liner: LMs are unreliable calculators but reliable coders. When the answer needs determinism and precision — arithmetic, exact data manipulation, deterministic transforms — emit code and run it. When the answer needs judgment, taste, or open-ended synthesis, reason in natural language. The cost of getting this gate wrong is silent: prose arithmetic hallucinates a plausible-looking wrong number, and over-coding a judgment task burns a sandbox round-trip for nothing.

This is an enhancement overlay. DSPy already gives you dspy.ProgramOfThought (PoT) — the mechanism for write-then-execute. What it does not give you is the decision rubric for when to reach for it. That rubric is this skill. Cross-link the sibling [[agentsop-output-format-by-model]] (which decides how code-shaped content should be serialized) and [[agentsop-test-fix-loop]] (which closes the execute → error → retry loop).

1. 何时激活 (When to activate)