The Personal Agent Ontology: Every Entity Explained

A complete walkthrough of all 115 classes, 173 properties, and 75 named individuals across 9 modules — the formal domain model behind every personal AI agent

February 24, 2026

25 min read

Deep Dive

📺 Watch the Full Deep Dive Video

17-minute narrated walkthrough of every PAO module with entity relationship diagrams.

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This is the companion reference for our deep-dive video on the Personal Agent Ontology (PAO). While our introductory post covered what the PAO is and why it matters, this guide walks through every class in every module — a complete entity-by-entity reference for agent architects and ontology engineers.

The PAO is a formal OWL 2 DL ontology aligned to BFO 2020 that maps the converging domain model of personal AI agents. It was created by analyzing implementations like OpenClaw, Claude Code, Letta, and the Model Context Protocol.

PAO at a Glance

115

Classes

138

Object Properties

Data Properties

Named Individuals

SHACL Shapes

128

Competency Questions

Module 1: Agent — Who Participates

The Agent module defines who acts in agent systems. Every entity that can participate in conversations, invoke tools, or hold beliefs descends from Agent.

Class	Description	Key Relationships
`Agent`	Base class for all participants	hasRole, belongsTo, holdsDesire, heldBelief
`AIAgent`	An agent powered by a foundation model	usesModel → FoundationModel, hasPersona → Persona
`HumanUser`	A human person interacting with AI systems	Aligned to foaf:Person, prov:Person
`SubAgent`	An AI agent spawned by another agent for delegated work	spawnedBy → AIAgent, delegatedTask → Task
`AgentRole`	A role an agent plays (researcher, coder, reviewer)	Aligned to BFO Role, prov:Role
`Organization`	A formal body or group of people	hasMember → Agent
`Persona`	Configured identity, behavior, and system prompt	Referenced by hasPersona from AIAgent

💡 Real-World Example

In OpenClaw, the main agent (AI Agent) is an AIAgent with a Persona defined in SOUL.md. When she spawns Karibe for research, that's a SubAgent with spawnedBy pointing to AI Agent and delegatedTask pointing to the research task.

Module 2: Session — The Conversation Stack

The Session module models conversation as a five-layer stack, each with distinct architectural concerns.

Core Conversation Classes

Class	Description	Key Properties
`Conversation`	Coherent dialogue thread spanning multiple sessions	hasConversationId
`Session`	Bounded period of interaction	hasContextWindow, partOfConversation
`Turn`	Single speaker contribution within a session	hasMessage, inSession, hasDialogAct
`Message`	Textual/structured content of a turn	hasContentBlock, sentViaChannel
`ContentBlock`	Typed segment of a message (text, code, image, tool call)	hasContentBlockType, blockSequenceIndex

Context Management

Class	Description
`ContextWindow`	Finite attention resource with hasTokenCapacity and hasTokensUsed
`CompactionEvent`	Context window compressed by summarizing prior turns
`CompactionDisposition`	Records fate of individual items during compaction

Channels

Class	Description
`CommunicationChannel`	Configured endpoint for agent-user dialogue
`ChannelType`	CLI, Messaging, WebChat, APIChannel, VoiceChannel, EmailChannel

Dialog Pragmatics (DIT++ Theory)

Class	Description
`DialogAct`	Pragmatic classification of a turn's communicative intent
`CommunicativeFunction`	Purpose: requesting, confirming, topic change
`CommonGround`	Accumulated shared knowledge between participants
`GroundingAct`	Contributing evidence to the common ground
`AcceptanceEvidence`	Proof that a participant acknowledged a proposition
`ClarificationRequest`	Request for additional info to resolve ambiguity

Status Classes

Class	Description
`SessionStatus`	Active, Suspended, Completed, Error
`SessionStatusTransition`	Records session state changes
`ContentBlockType`	Text, Code, Image, ToolCall, ToolResult
`ItemFate`	Retained, Summarized, Dropped (during compaction)

Module 3: Memory — Cognitive Architecture

Drawing from Letta's MemGPT, the CoALA framework, and LangMem's cognitive science framing, the Memory module defines four tiers and six operations.

Memory Tiers

Tier	Description	Analogy
`WorkingMemory`	Active context window contents, volatile	RAM
`EpisodicMemory`	Time-situated experiences and interaction histories	Diary
`SemanticMemory`	Generalized facts, knowledge, beliefs	Encyclopedia
`ProceduralMemory`	Learned action policies, skills, patterns	Muscle memory

Memory Items

Class	Description	Stored In
`MemoryItem`	Base class for stored information	Any MemoryTier
`Episode`	Temporally bounded cluster of related events	EpisodicMemory only
`Claim`	Proposition with confidence + evidence + provenance	SemanticMemory
`MemoryBlock`	Structured key-value data (Letta pattern)	WorkingMemory

Memory Operations

Operation	Description
`Encoding`	Write new information into a memory tier
`Retrieval`	Read information from a memory tier
`Consolidation`	Transform episodic memories into semantic knowledge
`Forgetting`	Remove or decay items by policy or request
`Rehearsal`	Strengthen items via repeated access

Memory Governance & Multi-Agent

Class	Description
`MemoryScope`	Private, Shared, Global visibility
`MemorySource`	Where a memory item originates
`SensitivityLevel`	Privacy classification
`RetentionPolicy`	How long items are kept (retentionPeriodDays)
`ErasureEvent`	Privacy-compliant deletion of memory items
`SharedMemoryArtifact`	Memory accessible to multiple agents (min 2)
`MemoryWriteConflict`	Concurrent write conflict on shared memory

Module 4: Tool — The Action Layer

Class	Description	Key Properties
`Action`	Intentionally caused event (subclass of Event)	performedBy → Agent
`ToolInvocation`	Actual call to a tool (subclass of Action)	producedToolResult, partOfInvocationGroup
`ToolResult`	Typed output artifact from a tool call	—
`ToolInvocationGroup`	Groups parallel tool calls within a turn	groupedInTurn → Turn
`ExternalService`	External system exposing capabilities	—
`ServiceCapability`	Base for discoverable capabilities	—
`ServiceToolCapability`	Provides a tool for invocation	—
`ServiceResourceCapability`	Provides a data resource	—
`ServicePromptCapability`	Provides a prompt template	—
`CapabilityDiscoveryEvent`	Agent discovers service capabilities	discoveredCapability, discoveryAgainstService
`ServiceConnection`	Runtime connection to a service	connectsToService, hasConnectionStatus
`Integration`	Configured connection	hasIntegrationStatus
`Hook`	Interceptor that can modify/block tool calls	hookTriggeredExecution
`HookExecution`	Event when a hook fires	interceptsInvocation → ToolInvocation

Module 5: Permission — Governance as Architecture

Class	Description
`PermissionPolicy`	Governs tool access (ODRL-aligned)
`PermissionMode`	Enforcement level: strict ↔ permissive
`SafetyConstraint`	Non-negotiable behavioral limits (appliesTo → Agent)
`SandboxPolicy`	Filesystem and network restrictions
`ConsentRecord`	Data subject's consent (consentPurpose, consentSubject)
`AuditLog`	Container for audit entries
`AuditEntry`	Authorization decision record with rationale
`AuthorizationDecision`	Allowed, Denied, Escalated
`ComplianceStatus`	Did invocation comply with policies?
`Checkpoint`	Decision point requiring human approval
`CheckpointDecision`	Approved, Rejected, Deferred

Module 6: Interaction — BDI Cognitive Architecture

Drawing from the Belief-Desire-Intention model in philosophy of mind, this module gives agents a vocabulary for why they act.

BDI Core

Class	Description	Key Properties
`Belief`	Proposition held to be true	heldBelief, considersBelief
`Desire`	Desired state or outcome	holdsDesire, considersDesire
`Intention`	Committed goal the agent will pursue	justifiesIntention
`Deliberation`	Reasoning process: beliefs + desires → intentions	considersBelief, considersDesire, producesIntention
`Justification`	Evidence supporting an intention	justifiesIntention → Intention

Goals, Plans & Tasks

Class	Description
`Goal`	High-level objective
`Plan`	Ordered sequence of actions to achieve a goal (achievesGoal)
`Task`	Individual unit of work within a plan
`TaskStatus`	Pending, InProgress, Blocked, Done, Failed
`TaskStatusTransition`	Records task state changes

Events

Class	Description
`Event`	Base class for all occurrences
`Observation`	Agent receives environmental feedback (inSession)
`StatusTransition`	Base for state changes

Module 7: Identity — Model Provenance

Class	Description	Key Properties
`FoundationModel`	Model family (e.g., Claude 4, GPT-4o)	hasModelId, hasModelVersion, hasProvider, deployedAs
`ModelProvider`	Organization serving models (Anthropic, OpenAI)	—
`ModelDeployment`	Running model endpoint configuration	—
`ModelInvocation`	Event: model produces output for a turn	invokedOnDeployment, modelInvocationForTurn, hasGenerationConfig
`GenerationConfiguration`	Temperature, top_p, max_tokens	—

Module 8: Deployment — Scheduling & Automation

Class	Description	Key Properties
`Schedule`	Binds a recurrence to an action	schedulesAction, hasRecurrencePattern, activatedBy
`RecurrencePattern`	When to fire: cron, interval, or calendar	hasCronExpression, hasIntervalSeconds
`Trigger`	Base activation condition	—
`CronTrigger`	Activates on cron schedule	—
`IntervalTrigger`	Activates at fixed intervals	—
`EventTrigger`	Activates on external event/webhook	—
`ScheduledExecution`	Individual run of a schedule	executionOf, hasExecutionOutcome, initiatedSession
`ScheduleStatus`	Active, Paused, Completed	—
`ExecutionOutcome`	Success, Failure, Skipped	—
`ConcurrencyPolicy`	Skip, Queue, Replace on overlap	—

Module 9: Provenance — Error Recovery & Observability

Error Recovery

Class	Description
`ErrorRecoveryEvent`	Failure occurrence with hasFailureType
`FailureType`	Timeout, AuthError, RateLimit, ParseError, NetworkError
`RetryAttempt`	Retry of a failed operation
`ReplanEvent`	Generate new plan after failure
`RollbackEvent`	Revert changes from failed operation
`ReliabilityIncident`	Broader failure/degradation event

Observability

Class	Description
`OperationalMetric`	Named metric type (hasMetricName)
`MetricObservation`	Recorded data point (observesMetric, hasMetricValue, observedOnEntity)

75 Named Individuals

The PAO uses owl:oneOf closed enumerations for status classes. Key enumeration values include:

SessionStatus: Active, Suspended, Completed, Error
TaskStatus: Pending, InProgress, Blocked, Done, Failed
ChannelType: CLI, Messaging, WebChat, APIChannel, VoiceChannel, EmailChannel
AuthorizationDecision: Allowed, Denied, Escalated
MemoryScope: Private, Shared, Global
FailureType: Timeout, AuthError, RateLimit, ParseError, NetworkError
CommunicativeFunction: Request, Inform, Confirm, Reject, TopicChange
ItemFate: Retained, Summarized, Dropped
ComplianceStatus: Compliant, NonCompliant, Unknown
ConnectionStatus: Connected, Disconnected, Error
PermissionMode: Strict, Permissive, Ask
ExecutionOutcome: Success, Failure, Skipped
ConcurrencyPolicy: Skip, Queue, Replace
SensitivityLevel: Public, Internal, Sensitive, Restricted

The Unified Picture

All nine modules connect through the Agent class at the center:

Agent → Session: Agents participate in sessions, which contain turns and messages
Session → Memory: WorkingMemory maps to ContextWindow; Episodes derive from turns; Claims consolidate from episodes
Turn → Tool: Turns trigger ToolInvocations that produce ToolResults
Tool → Permission: Every invocation passes through PermissionPolicy to generate AuditEntries
Agent → Interaction: Beliefs, Desires, and Intentions inform deliberation and goal pursuit
Turn → Identity: ModelInvocation tracks which model/deployment produced each turn
Schedule → Session: ScheduledExecution can initiate new sessions automatically
Any Event → Provenance: ErrorRecoveryEvent connects to failures in tools, models, or schedules

✅ Formal Guarantees

12 AllDisjointClasses groups • 4 DisjointUnion axioms • 0 unsatisfiable classes • 1,332 test assertions passing • Every class aligned to BFO 2020

Real-World Mappings

Letta (MemGPT)

Core Memory Blocks → MemoryBlock in WorkingMemory
Message Buffer (FIFO) → EpisodicMemory + CompactionEvent
Recall Memory → EpisodicMemory (full searchable history)
Archival Memory → SemanticMemory
memory_insert tool → Encoding operation
Self-editing agent → Deliberation → Encoding

Claude Code / OpenClaw

Main agent session → Session + AIAgent
Sub-agent spawning → SubAgent (spawnedBy, delegatedTask)
AGENTS.md / SOUL.md → Persona
Tool calls (read, write, exec) → ToolInvocation → ToolResult
Permission ask modes → PermissionPolicy + PermissionMode
[compacted] messages → CompactionEvent + CompactionDisposition
Telegram / CLI channels → CommunicationChannel + ChannelType
Cron-triggered tasks → Schedule + CronTrigger

Model Context Protocol (MCP)

Discovery → CapabilityDiscoveryEvent
Authentication → ServiceConnection
Invocation → ToolInvocation
Disconnect → ConnectionStatus = Disconnected

References

PAO Full Documentation — Browsable HTML with all 115 classes
PAO Blog Post — Original announcement
PAO Persistent URL — OWL 2 DL in Turtle/JSON-LD/OWL-XML
BFO 2020 — Basic Formal Ontology (ISO 21838-2)
MemGPT Paper — Virtual context management for LLMs
CoALA Framework — Cognitive architectures for language agents
Letta — Stateful agents with tiered memory
OpenClaw — Open-source personal AI agent platform
Claude Code — Anthropic's agentic coding tool
Model Context Protocol — Standard for LLM-tool integration
PROV-O — W3C provenance ontology
ODRL — W3C permissions vocabulary