skills/legal/article-summary/SKILL.md
Generates structured 500-800 word summaries of legal articles distilling thesis, methodology, arguments, authorities, conclusions, and significance. Triggers when summarizing legal scholarship, reviewing law review articles, preparing literature reviews, or triaging articles for full reading.
npx skillsauth add casemark/skills article-summaryInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Produces a structured summary (500–800 words) of a legal article that works as both a standalone reference and a read/skip triage tool.
| Field | Content | |-------|---------| | Citation | Bluebook or jurisdiction-appropriate format | | Author(s) | Name(s) and affiliation if relevant | | Publication | Journal/venue and date | | Article Type | Doctrinal / Empirical / Policy / Comparative / Theoretical |
1. Thesis & Research Question — Central argument in 1-2 sentences. Identify the legal problem: doctrinal gap, policy critique, empirical question, or theoretical development.
2. Methodology & Approach — Method (case law analysis, statutory interpretation, comparative, empirical, theoretical). Note dataset, jurisdiction scope, or time period if applicable.
3. Key Arguments & Findings — Major points in logical sequence mirroring the author's reasoning. Use numbered list for distinct arguments. Preserve the author's emphasis; reflect counterarguments if substantially treated.
4. Authorities & Precedents — Key cases, statutes, regulations, or principles forming the analytical foundation. Note usage: supporting, distinguishing, or criticizing.
5. Conclusions & Recommendations — Separate analytical findings (evidence-supported) from normative proposals (reform/practice changes). Note stated limitations or areas for further research.
6. Significance & Implications — Relationship to existing scholarship (confirms, challenges, extends). Practical impact on practice, judicial decisions, legislation, or regulatory policy. Novel contributions.
tools
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development
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data-ai
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testing
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