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Agent Intent Protocol (AIP)

Minimal semantic interaction objects for agent runtimes.

AIP is the interaction layer repository in the Digital Biosphere Architecture. It defines machine-readable intent, action, and result objects that can pass between persona-oriented systems, governance checkpoints, runtimes, and audit layers. It is a layer repo, not a canonical architecture hub.

Role

agent-intent-protocol is the interaction layer repository in the Digital Biosphere Architecture.

It defines machine-readable intent, action, and result objects.

It is a layer repo, not a canonical architecture hub.

Not this repo

• not a transport protocol
• not the governance layer
• not the execution-integrity kernel
• not the audit record format
• not the architecture hub

Start here

• spec/
• schema/
• examples/
• conformance/
• docs/fdo-relation-note.md
• digital-biosphere-architecture

Depends on

• POP handles persona identity.
• Token Governor handles runtime constraints and policy.
• MVK handles execution integrity.
• ARO-Audit handles evidence and receipts.

Status

• working draft
• semantic interaction layer only
• intended to compose with adjacent layers

Architecture Position

AIP contributes the Interaction Layer in the Digital Biosphere Architecture ecosystem.

flowchart LR
    Persona["Persona"] --> Intent["Intent Object"]
    Intent --> Governance["Governance Check"]
    Governance --> Execution["Execution"]
    Execution --> Evidence["Evidence"]

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Non-goals

• AIP is not a chat format.
• AIP is not a transport layer.
• AIP is not a full agent orchestration framework.
• AIP is not a permission or identity substitute.

Core Objects

Intent Object

An agent_intent object declares what the actor wants to achieve and under what constraints.

{
  "schema_version": "0.1.0-draft",
  "object_type": "agent_intent",
  "intent": {
    "summary": "Find round-trip flight options from Shanghai to Singapore for next week"
  },
  "actor_ref": "pop://personas/travel-assistant",
  "constraints": {
    "max_budget_usd": 900,
    "approval_required": false
  }
}

Action Object

An agent_action object declares a specific operation proposed or executed by the actor.

{
  "schema_version": "0.1.0-draft",
  "object_type": "agent_action",
  "action": {
    "name": "call_search_tool",
    "summary": "Query the local flight-search adapter"
  },
  "actor_ref": "pop://personas/travel-assistant",
  "execution_mode": "proposal"
}

Result Object

An agent_result object declares the status and references to outputs or evidence produced by the run.

{
  "schema_version": "0.1.0-draft",
  "object_type": "agent_result",
  "status": "completed",
  "actor_ref": "pop://personas/travel-assistant",
  "correlation_id": "trip-search-001"
}

Repository Layout

• spec/ contains the draft protocol text.
• schema/ contains JSON Schema drafts for the three core object types.
• examples/ contains worked examples.
• conformance/ contains valid and invalid fixtures.
• scripts/validate_examples.py validates the examples and fixtures.
• tests/ contains a minimal pytest surface.

Conformance

Run the lightweight validator:

python3 scripts/validate_examples.py

Run the minimal test surface:

pytest

FDO-facing Note

For FDO-related positioning, see docs/fdo-relation-note.md.

Architecture Navigation

• Digital Biosphere Architecture
• Persona Object Protocol
• Agent Intent Protocol
• Token Governor
• MVK
• ARO Audit