analyze-case

Analyze court opinions to extract parties, entities, and related litigation.

Updated Feb 18, 2026

Search Tags:#legal research #litigation analysis #court case analysis #opinion extraction #judge analysis

Ready to run

npx skills add https://github.com/tcole333/ithildin --skill analyze-case

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: analyze-case
Source: https://github.com/tcole333/ithildin/tree/main/.claude/skills/analyze-case
Command: npx skills add https://github.com/tcole333/ithildin --skill analyze-case

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python, uvicorn, courtlistener, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the process of deep analysis in court cases, allowing users to extract and trace related litigation efficiently.

Core Features & Use Cases

Full Opinion Analysis: Extracts structured intelligence from complex litigation documents.
Party and Entity Identification: Identifies named parties, corporate entities, and government agencies.
Factual and Monetary Information Extraction: Extracts specific factual allegations, monetary figures, and dates.
Related Litigation Tracing: Searches for related cases and traces the citation graph.
Judge Analysis: Analyzes judges' careers, investments, and potential conflicts of interest.
Cross-Reference Against Investigation: Cross-references findings against an investigation database.
Spawn Follow-Up Leads: Spawns new leads based on findings and related cases.

Quick Start

Use the analyze-case skill to extract all relevant information from the court opinion for case '67890123'.

Frequently Asked Questions about analyze-case

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I extract structured intelligence from court opinions?▼

Court opinion analysis extracts structured intelligence by identifying named parties, corporate entities, and factual allegations from litigation documents. It utilizes Python to process retrieved data and surface specific monetary figures, dates, and relevant case facts.

What is the best way to trace related litigation and citation graphs?▼

Tracing related litigation involves searching for connected cases and mapping the citation graph from a specific court opinion. This process identifies related legal actions and spawns new leads based on the findings of the initial case analysis.

Can I analyze a judge's career and potential conflicts of interest from court case data?▼

Judge analysis evaluates a judge's career history, investments, and potential conflicts of interest using extracted court case data. It cross-references these findings against an investigation database to identify relevant biases or financial overlaps.

Do I need a courtlistener API access to analyze court case opinions?▼

Yes, courtlistener API access is required for court case opinion analysis. The Skill relies on this dependency to retrieve case data, which is then processed locally using Python and uvicorn to extract structured litigation intelligence.

How does cross-referencing extracted case entities against an investigation database work?▼

Cross-referencing case entities compares extracted parties, corporate entities, and government agencies against an existing investigation database. This mechanism validates findings, identifies overlapping suspects, and spawns follow-up leads for deeper legal research.