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Jurisrank Argentine Supreme Court Analysis Adrian Lerer

Organization
ThomasMoreAI
jurisrank-argentine-supreme-court-analysis-adrian-lerer

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.

Overview

PublisherThomasMoreAI
Repositorylegal-skills-open
Skill namejurisrank-argentine-supreme-court-analysis-adrian-lerer
Stars
97
Forks
13
Bundled files
Instructions only
LicenseCC-BY-4.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by ThomasMoreAI on GitHub. Read the source before you install it.

Installation

Install the Jurisrank Argentine Supreme Court Analysis Adrian Lerer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ThomasMoreAI/legal-skills-open/tree/main/ar/litigation/skills/jurisrank-argentine-supreme-court-analysis-adrian-lerer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
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
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Jurisrank Argentine Supreme Court Analysis Adrian Lerer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Jurisrank Argentine Supreme Court Analysis Adrian Lerer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Jurisrank Argentine Supreme Court Analysis Adrian Lerer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

AlgorithmPurpose
JurisRankPageRank + temporal decay — recent citations weighted higher
RootFinderAncestral Borrowing Analysis Network — traces doctrinal genealogy
Legal-MemespacePrincipal Component Analysis — maps multidimensional doctrine

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

ScoreMeaningRecommendation
> 0.8Leading case — highest citation authorityCite first, with score
0.6–0.8Widely cited — strong precedential weightCite with score
0.4–0.6Relevant — moderate authorityCite with note
< 0.4Limited authority — outlier or isolatedOrientation only
Not foundNo network presence detectedDeclare absence of precedent

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

Frequently asked questions

What does the Jurisrank Argentine Supreme Court Analysis Adrian Lerer AI skill do?

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.

Why use Jurisrank Argentine Supreme Court Analysis Adrian Lerer on TypingMind?

Because you install it once and use it with any model. Jurisrank Argentine Supreme Court Analysis Adrian Lerer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Jurisrank Argentine Supreme Court Analysis Adrian Lerer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ThomasMoreAI/legal-skills-open/tree/main/ar/litigation/skills/jurisrank-argentine-supreme-court-analysis-adrian-lerer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Jurisrank Argentine Supreme Court Analysis Adrian Lerer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Jurisrank Argentine Supreme Court Analysis Adrian Lerer?

As many as you like. As long as a model supports skills, you can use Jurisrank Argentine Supreme Court Analysis Adrian Lerer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Jurisrank Argentine Supreme Court Analysis Adrian Lerer AI skill free?

Yes. It is published on GitHub by ThomasMoreAI under the CC-BY-4.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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