AI Contract Sentinel

Risk triage for AI-generated or AI-reviewed contracts.

Version: 1.0.0 | License: MIT | Status: production-oriented v1 foundation

Problem

Contracts increasingly include AI-generated clauses, but parties need transparent checks for hallucinated obligations, missing provenance, and risky automated edits.

What this project solves

A contract review manifest checker that validates source documents, reviewer role, clause risk tags, and unresolved human review items.

AI Contract Sentinel ships as a small, dependency-free CLI and library. It validates a domain-specific JSON packet, emits actionable findings, and gives contributors a concrete surface for adding adapters, richer checks, schemas, and integrations.

Who it is for

Legal ops teams, open legal tech contributors, procurement teams.

Quick start

npm test
npm start -- sample

Analyze your own packet:

ai-contract-sentinel ./packet.json

Or pipe JSON:

cat packet.json | node src/cli.js

Example packet

{
  "contract": {
    "id": "msa-42",
    "jurisdiction": "NY"
  },
  "review": {
    "aiGeneratedClauses": [
      "data_processing"
    ],
    "humanReviewer": ""
  },
  "risks": [
    {
      "clause": "indemnity",
      "severity": "medium"
    }
  ]
}

Library usage

const { analyze } = require("./src/index.js");

const report = analyze({
  "contract": {
    "id": "msa-42",
    "jurisdiction": "NY"
  },
  "review": {
    "aiGeneratedClauses": [
      "data_processing"
    ],
    "humanReviewer": ""
  },
  "risks": [
    {
      "clause": "indemnity",
      "severity": "medium"
    }
  ]
});
console.log(report.summary);

v1 behavior

• Validates required fields for the domain packet.
• Scores readiness from 0 to 100.
• Reports missing or weak governance evidence.
• Suggests next actions and contributor extension points.
• Runs fully offline with no API keys and no network access.

Contribution map

Good first contributions:

• Add clause taxonomies.
• Add citation checkers.
• Add redline provenance.
• Add jurisdiction adapters.

Larger contributions:

• Add a JSON Schema and compatibility tests.
• Build import/export adapters for popular AI frameworks.
• Add real-world fixtures from public, non-sensitive examples.
• Improve scoring with transparent, documented heuristics.

Project principles

• Human agency over blind automation.
• Open standards over vendor lock-in.
• Auditable decisions over hidden magic.
• Privacy and safety as design constraints, not release notes.

GitHub Pages

The marketing site lives in site/index.html. Enable GitHub Pages from the site folder or use the included Pages workflow after publishing.

Security

This project does not process secrets by default. If you build adapters that touch production systems, keep least privilege, explicit consent, and auditable logs in the design.