legal-abductive-reasoning
legal-abductive-reasoning is a Structured reasoning & decision frameworks skill for AI agents, published by THUYRan in the Legal-Skills-Chinese repository on GitHub. Skillspace rates legal-abductive-reasoning F (51/100) and it passed the safety scan; the rating is based on static analysis only.
Legal abductive reasoning skill for generating and evaluating the most reasonable explanatory hypotheses when evidence is incomplete or facts are ambiguous. Combines Mill’s five methods (agreement, difference, joint method, residues, concomitant variation) for structured causal inference. Triggered when the user needs to “propose possible legal explanations,” “generate defense/prosecution hypotheses,” “evaluate multiple readings of evidence,” or “infer the best explanation from incomplete facts.” Applies to case analysis, evidence evaluation, disputes over rule application, causal inference, and similar scenarios.
- Grade
- F
- Quality
- 51 / 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.
Our review
- Architecture
- 69 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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