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jurisrank-argentine-supreme-court-analysis-adrian-lerer skill

by ThomasMoreAI·ThomasMoreAI/legal-skills-open·79 stars·Apache-2.0

Argentine Supreme Court citation network analysis using JurisRank — a peer-reviewed PageRank algorithm with temporal decay for measuring jurisprudential authority. Ranks precedents by citation influence, traces doctrinal evolution, and detects constitutional drift. Published methodology: JCLLT (DOI: 10.47852/bonviewJCLLT62027951). Activate with: which cases to cite, rank precedents, case authority, doctrinal evolution, Argentine Supreme Court, CSJN jurisprudence, citation network, leading case, legal research Argentina.

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Install the jurisrank-argentine-supreme-court-analysis-adrian-lerer skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.

git clone --depth 1 https://github.com/ThomasMoreAI/legal-skills-open.git /tmp/legal-skills-open
mkdir -p ~/.claude/skills
cp -r /tmp/legal-skills-open/ar/litigation/skills/jurisrank-argentine-supreme-court-analysis-adrian-lerer ~/.claude/skills/jurisrank-argentine-supreme-court-analysis-adrian-lerer
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In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

JurisRank — Argentine Jurisprudential Authority Analysis

What JurisRank Is

JurisRank is a computational tool for measuring the authority of Argentine court decisions through citation network analysis. Its methodology is peer-reviewed and published in the Journal of Computational Law and Legal Technology:

Lerer, I.A. (2026). "Computational Detection of Constitutional Drift:

Network Analysis and Semantic Measurement of Argentine Supreme Court

Jurisprudence (1922–2025)." *Journal of Computational Law and Legal

Technology.* DOI: 10.47852/bonviewJCLLT62027951

Academic validation: κ = 0.83 inter-coder reliability · k-fold cross- validation (k=5) · 73.2% mean accuracy · Monte Carlo simulations (n=1,000).

License: Creative Commons Attribution 4.0 International (CC BY 4.0)

Three Algorithms

Coverage

  • Argentine Supreme Court (CSJN) — 1922 to present
  • National and federal courts of appeals (Cámaras nacionales y federales)
  • Selected provincial supreme courts
  • Relevant international precedents cited by Argentine courts

Authority Score Interpretation

Use Cases

1. Selecting case law for briefs and memos

When multiple cases address the same issue, JurisRank identifies which carry the most authority in the citation network → cite the most influential first, in ranked order.

2. Doctrinal evolution analysis

Trace how CSJN or appellate court doctrine evolved on a specific topic. Identify whether the most recent decision continues or breaks from prior doctrine.

3. Adversarial jurisprudential due diligence

Verify whether precedents cited by opposing counsel are genuinely authoritative or low-influence outliers.

4. Constitutional drift detection

Detect shifts in citation patterns that signal doctrinal erosion or realignment — original application from the JCLLT paper.

Workflow

1. Identify topic or specific cases to analyze
2. Query JurisRank API:
   GET  https://api.jurisrank.com/v1/cases?query=<topic>
   POST https://api.jurisrank.com/v1/analyze-authority {"case_id": "..."}
3. Interpret Authority Score and citation network position
4. Apply RootFinder for genealogy if doctrinal evolution is needed
5. Produce ranked analysis with citation recommendations

Anti-Hallucination Rules

JurisRank implements groundedness verification per the Stanford Legal AI Benchmark (Magesh et al., 2024):

Before including any case in the analysis:

  • Confirm Authority Score > 0.0 (case exists in the network)
  • Verify jurisdiction matches the forum of the matter
  • Check temporal decay: has a more-cited posterior decision superseded it?
  • Verify the case actually supports the proposition — not just addresses the topic

Never cite a case not found in the JurisRank network without explicitly declaring it as unverified.

Output Format

JURISRANK ANALYSIS — [Topic]
Date: [date] | Tool: JurisRank (Lerer, 2026, JCLLT)

## RANKED PRECEDENTS BY AUTHORITY
| Case | Court | Year | Authority Score | Network Position |
|------|-------|------|----------------|-----------------|
| ...  | CSJN  | ...  | 0.92           | Leading case    |

## DOCTRINAL EVOLUTION
[Timeline: how doctrine developed]

## CITATION NETWORK
[Which cases cite each other; doctrinal clusters]

## RECOMMENDATION
[Which cases to cite · in what order · why]

About the Author

Ignacio Adrián Lerer is an Argentine attorney and independent researcher. JurisRank was developed as part of research on computational legal analysis published in peer-reviewed journals. The tool is registered with Argentina's DNDA (copyright registry) and has a patent application pending at INPI Argentina.

Contact: justitia.com.ar 39:["$","div",null,{"className":"relative z-10 mx-auto max-w-[1400px] px-4 pb-16 sm:px-8 lg:px-16","children":[["$","$L3d",null,{"skillId":"b02a0fed-5d2a-4e82-81c0-36f6f4cf1a80","skillTitle":"Argentine Supreme Court Analysis","skillStatus":"active","skillVisibility":"listed","slug":"jurisrank-argentine-supreme-court-analysis-adrian-lerer","shareToken":null,"settingsShareToken":null,"fileTree":["SKILL.md"],"textContents":{"SKILL.md":"$3e"},"fileSizes":{"SKILL.md":5694},"hasShowcase":false,"hasSandbox":true,"canEdit":false,"isAdmin":false,"demoFiles":[],"sandboxConfig":{"steps":[{"type":"files","filesRequired":false}]},"initialDependencies":[],"initialMcpServers":[],"initialOauthConnections":[],"initialAccessGrants":[],"showcase":null,"about":{"locale":"en","sections":[{"title":"What this skill does","body":"PageRank-based jurisprudential authority analysis for Argentine case law (CSJN, federal courts). Peer-reviewed methodology published in JCLLT (DOI: 10.47852/bonviewJCLLT62027951). Ranks precedents by citation network influence with temporal decay."},{"title":"How to use","body":"The best way to start is to try it live right here — run it against your own document or question to see exactly how it operates, without any setup. Once you're comfortable, download the skill files and drop them into any AI assistant — Claude (Anthropic), ChatGPT (OpenAI), Gemini (Google), or Mistral. The same skill file works across all of them, so you are never locked into a single provider."}],"requiredSkills":[],"dependentSkills":[],"author":{"name":"Ignacio Adrián Lerer

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