What is JACS?

JACS (JSON Agent Communication Standard) is a comprehensive framework designed to solve a critical problem in AI systems: How do agents communicate and collaborate securely with verifiable trust?

The Problem JACS Solves

As AI systems become more sophisticated, we're moving toward multi-agent architectures where different AI agents need to:

  • Exchange tasks and delegate work to each other
  • Create agreements and verify their completion
  • Share data with guaranteed authenticity
  • Maintain audit trails of decisions and actions
  • Establish trust without centralized authorities

Traditional approaches fall short because they lack:

  • Cryptographic integrity for agent communications
  • Standardized formats for agent interactions
  • Built-in versioning and audit trails
  • Support for multi-agent agreements and workflows

JACS Core Philosophy

🎯 Agent-First Design

JACS is built specifically for AI agent communication patterns, not as a general-purpose document signing system. It understands concepts like:

  • Agents with identities and capabilities
  • Tasks that can be delegated and tracked
  • Agreements between multiple parties
  • Versioning for iterative improvements

🔐 Trust Through Cryptography

Every JACS document includes:

  • Digital signatures proving authenticity
  • Hash verification ensuring integrity
  • Public key cryptography for identity verification
  • Timestamps for chronological ordering

📋 Standards-Based

JACS builds on proven standards:

  • JSON for universal compatibility
  • JSON Schema for structure validation
  • RFC 3339 timestamps for consistency
  • Standard cryptographic algorithms (RSA, Ed25519, post-quantum)

Key Concepts

Agents

An Agent is an autonomous entity with:

  • A unique identity (UUID)
  • Cryptographic keys for signing
  • Capabilities defined in services
  • The ability to create and verify documents

Documents

A Document is any JSON object that includes:

  • JACS header fields (ID, version, creator, etc.)
  • A cryptographic signature
  • A hash for integrity verification
  • Business logic specific to the document type

Tasks

A Task is a special document type representing:

  • Work to be performed
  • Success/failure criteria
  • Input/output specifications
  • Delegation and completion tracking

Agreements

An Agreement is a mechanism for:

  • Multiple agents to consent to terms
  • Tracking signatures from all required parties
  • Ensuring all participants have signed before proceeding
  • Creating binding commitments between agents

How JACS Works

graph TD
    A[Agent A] -->|Creates Task| T[JACS Task Document]
    T -->|Contains| S[Digital Signature]
    T -->|Contains| H[SHA256 Hash]
    T -->|Contains| M[Metadata]
    
    A -->|Sends to| B[Agent B]
    B -->|Verifies| T
    B -->|Signs Agreement| AG[Agreement Document]
    AG -->|Returns to| A
  1. Agent A creates a task document with their requirements
  2. The document is signed with Agent A's private key
  3. A hash is calculated for integrity verification
  4. Agent B receives and verifies the signature and hash
  5. Agent B can create an agreement to accept the task
  6. Both agents have a verifiable record of the interaction

Real-World Examples

🤖 AI Content Pipeline

Content Agent → Research Agent → Review Agent → Publishing Agent

Each handoff includes signed task documents with clear requirements and deliverables.

📊 Data Processing Workflow

Data Ingestion Agent → Processing Agent → Validation Agent → Storage Agent

Each step is tracked with verifiable completion certificates and quality metrics.

🔍 Multi-Agent Analysis

Query Agent → Research Agent → Analysis Agent → Reporting Agent

Complex analysis tasks are broken down with clear accountability for each step.

Benefits Over Alternatives

FeatureJACSTraditional APIsGeneral Signing
Agent Identity✅ Built-in❌ Custom implementation❌ Not agent-focused
Task Management✅ Native support❌ Application-specific❌ Not applicable
Multi-Party Agreements✅ Core feature❌ Complex to implement⚠️ Possible but difficult
Audit Trails✅ Automatic❌ Manual logging⚠️ Basic signing only
Schema Validation✅ JSON Schema❌ Custom validation❌ No structure
Versioning✅ Built-in❌ Manual versioning❌ Not supported
Cross-Platform✅ JSON everywhere⚠️ Protocol dependent⚠️ Format dependent

When to Use JACS

✅ Perfect for:

  • Multi-agent AI systems
  • Task delegation and tracking
  • Audit trail requirements
  • Cross-organization AI collaboration
  • Compliance-critical AI applications
  • Research environments with multiple AI models

⚠️ Consider alternatives for:

  • Simple single-agent systems
  • Real-time streaming data
  • High-frequency micro-transactions
  • Systems where trust is not a concern

Next Steps

Ready to dive deeper? Continue with: