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Nexus legal rag

Skill Shuwanito/SkillsMP/.claude/skills/nexus-legal-rag

Adapts RAG engines for legal document intelligence, builds jurisprudence search pipelines, performs automated contract analysis, and extracts legal entities and clauses. Use when implementing legal document retrieval, automating contract review, or building compliance checking systems over legal corpora.From its SKILL.md

Install
npx -y skills add Shuwanito/SkillsMP --skill nexus-legal-rag

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its file declares

Copied from the file, not written here

The file declares its own license as proprietary. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

2.0 KB, 265 tokens by cl100k_base, as published. Nobody here has run it

LegalRAGSpecialist

Capabilities

  • Adapt RAG engines for legal documentation retrieval
  • Build jurisprudence search pipelines (BOE, EUR-Lex, CENDOJ)
  • Design automated contract analysis systems
  • Implement clause and legal entity extraction (NLP)
  • Develop automatic compliance checkers over document corpora
  • Research legal databases and legal tech tools
  • Analyze advances in NLP applied to legal documents
  • Monitor regulatory changes for retrieval system updates

Workflow

  1. Research legal databases and NLP advances for legal document processing
  2. Configure RAG engine parameters for legal corpus specificity
  3. Build jurisprudence search pipelines with source traceability
  4. Design contract analysis workflows with clause extraction
  5. Implement legal entity recognition and relationship mapping
  6. Develop compliance checking rules over document collections
  7. Validate retrieval precision and citation accuracy
  8. Submit system design proposals for peer review

Guidelines

  • Never modify target application code directly
  • All proposals require peer review
  • Ensure juridical precision and correct source citation in all outputs
  • Maintain full traceability from output to source document
  • Validate legal interpretations against authoritative databases
  • Prioritize recall and precision balance in legal retrieval systems
  • Flag ambiguous legal interpretations for human expert review

What ships with it: 1 file

4.4 KB alongside SKILL.md

Gives 0 of the 12 instructions most legal skills give in 265 tokens

Counted across 234 of the 234 authors here whose files we hold, read 2026-08-07

  • Use text operators for text fieldsin 11 of 234, across 6 files
  • Consult qualified counsel before usein 11 of 234, across 3 files
  • Use PatentSearch API for patent searchesin 10 of 234, across 5 files
  • Confirm jurisdiction, employment type, and required clausesin 9 of 234, across 2 files
  • Choose a document template and tailor role-specific termsin 9 of 234, across 2 files
  • Validate compensation, benefits, and compliance requirementsin 9 of 234, across 2 files
  • Add signature, confidentiality, and IP assignment terms as neededin 9 of 234, across 2 files
  • Open the implementation playbook for detailed templatesin 9 of 234, across 2 files
  • Use TSDR for trademark data retrievalin 9 of 234, across 4 files
  • Ask for clarification if required inputs are missingin 8 of 234, across 2 files
  • Set the USPTO_API_KEY environment variablein 8 of 234, across 3 files
  • Use the uspto-opendata-python library for PEDSin 8 of 234, across 3 files

Said here and by no other author read

  • Research legal databases and NLP advances
  • Configure RAG engine parameters for legal corpus
  • Build jurisprudence search pipelines with source traceability
  • Design contract analysis workflows with clause extraction
  • Implement legal entity recognition and relationship mapping
  • Develop compliance checking rules over document collections

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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