evidence-evaluation

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

Trigger this skill when evidence materials in a case need to be assessed for authenticity, legality, and relevance (the “three attributes” of evidence / 三性), as well as for probative value. Typical trigger scenarios include, but are not limited to: - After a party or counsel submits evidence, assessing whether the court is likely to admit it - Responding to and analyzing the opposing party’s cross-examination / challenge opinions on one’s own evidence - Conducting a comprehensive evaluation of all evidence in the case to determine whether facts to be proved are established - Determining whether evidence meets the applicable standard of proof (e.g., high degree of probability, beyond reasonable doubt) - Identifying weak links in the chain of evidence and proposing reinforcement recommendations - Assessing the validity of special forms of evidence such as electronic data, expert opinions, and witness testimony - Identifying and arguing exclusion of illegally obtained evidence

Grade

F

Quality

45 / 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.

This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.

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