evidence-argument-chain

evidence-argument-chain is a Legal research & case law skill for AI agents, published by THUYRan in the Legal-Skills-Chinese repository on GitHub. Skillspace rates evidence-argument-chain F (45/100) and it passed the safety scan; the rating is based on static analysis only.

Trigger this skill when multiple pieces of evidence in a case must be systematically mapped to legal argumentative claims. Typical trigger scenarios include: preparing litigation documents (complaint, answer, counsel's brief) that require a complete evidence–claim correspondence; organizing the evidence list before trial and clarifying the purpose of proof for each item; reorganizing the evidence chain after the opposing party raises rebuttals; cases with multiple disputed issues where evidence must be grouped under different argumentative claims; assessing whether existing evidence sufficiently supports all claims and identifying weak links and gaps in the evidence chain. The core of this skill is to build a complete mapping of "claim → elements → evidence → probative-value assessment," ensuring every legal claim is adequately supported by evidence, every piece of evidence has a clear purpose of proof, and the overall argumentative chain is logically rigorous and hierarchically clear.

Grade

F

Quality

45 / 100

Safety

Passed

GitHub stars

826

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

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