counterfactual-reasoning

counterfactual-reasoning is a Structured reasoning & decision frameworks skill for AI agents, published by THUYRan in the Legal-Skills-Chinese repository on GitHub. Skillspace rates counterfactual-reasoning D (56/100) and it passed the safety scan; the rating is based on static analysis only.

Trigger this skill when you need to assess how legal outcomes would differ if a given fact, act, or condition did not exist or were altered. Typical trigger scenarios include: causation determinations (whether harm would still have occurred without the act), allocation of fault and liability shares, delimiting the scope of damages, calculating contract breach losses, hypothetical legality tests for administrative acts, assessing interruption of criminal causation, and legislative impact assessment. The core method is to construct a 'counterfactual world' that differs from the actual world only in the target variable, compare outcome differences between the two worlds, and thereby determine the target variable's contribution to the result.

Grade

D

Quality

56 / 100

Safety

Passed

GitHub stars

826

Unproven: rated by static analysis only, not yet compared head-to-head.

Our two independent classifiers differ on this skill's category, so treat the placement as provisional.

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