Coming from elsewhere
Harn's vocabulary doesn't always match what you'd read in OpenAI's, Anthropic's, Flue's, LangGraph's, Inngest's, Mastra's, or the ACP/A2A/MCP specs. This page is the cross-reference.
If a term in your home system collides with a Harn term, find your row in the table for that system.
OpenAI Agents SDK
| OpenAI term | Harn equivalent | Notes |
|---|---|---|
Agent (class) | agent_loop(harness, ...) invocation, or a persona | OpenAI's Agent bundles instructions, tools, and output type; the closest Harn shape is a configured agent_loop call site. |
Runner.run(...) | one agent_loop(harness, ...) invocation | One OpenAI "turn" wraps many model round-trips. One Harn agent loop invocation does the same. |
| "turn" | Harn prompt turn / agent_loop | OpenAI's "turn" is the outer cycle (one user request → final answer), not Harn's per-iteration counter. |
| "model roundtrip" (unnamed) | Harn iteration | The inner unit. |
max_turns | max_iterations | Both bound a budget, but the nouns are off-by-one — OpenAI counts outer SDK invocations, Harn counts inner LLM calls. |
Session (SQLiteSession("id")) | session_id + harness.agent.open(id) | Direct match. |
handoff | persona handoff or spawn_agent | Direct match in shape. |
input_guardrails / output_guardrails | agent_input_guardrail + tool middleware + completion gates | Harn exposes input guardrails as a named pre-loop bookend; output checks use completion gates, judges, validators, and tool middleware. |
Anthropic Claude Agent SDK
| Anthropic term | Harn equivalent | Notes |
|---|---|---|
| "agent loop" | agent_loop | Direct vocabulary match. |
query() / ClaudeSDKClient | agent_loop(harness, ...) | Pass history or reuse session_id for stateful prompt turns. |
AssistantMessage, TextBlock (typed stream) | transcript events | Anthropic streams typed messages; Harn streams typed transcript events. |
| Session resumption | harness.agent.open(id) + transcript continuity | Direct match. |
| "hook" | register_tool_hook, register_session_hook, register_reminder_provider | Harn's hook registry is the richer version. |
Anthropic and Harn align closely on agent-loop vocabulary; this is the easiest mapping in the table.
LangGraph
| LangGraph term | Harn equivalent | Notes |
|---|---|---|
Node | stage (workflow) | Both encode a unit of computation. |
Edge | workflow transition | Same shape; Harn doesn't expose it as a separate noun. |
State (typed dict) | Workflow artifacts + optional state-channel proposal | LangGraph's strict typed-dict-with-reducers is not Harn's default state model. The v0 design is tracked in Workflow state channels. |
Channel | proposed workflow state channel | LangGraph channels are typed slots with merge reducers. Harn's agent_channels are something else entirely (pub/sub for agent-to-agent communication). |
Thread (thread_id) | session_id | Direct match. |
super-step | iteration | LangGraph's super-step is one parallel barrier; semantically Harn's per-iteration. |
checkpoint / checkpointer | session bundle, snapshot | Direct match. |
interrupt / Command(resume=...) | agent_await_resumption | Direct match. |
LangGraph's biggest Harn-doesn't-have-this-by-default is typed-state channels with reducers. Harn's v0 design keeps artifacts and transcripts as the common path, then adds explicit workflow state channels for structured fan-out/reduce cases.
Flue
Flue and Harn both put agents inside a harness and separate continuing agents from finite workflows. Flue is a TypeScript framework. Harn is a language and runtime with host adapters.
| Flue term | Harn equivalent | Notes |
|---|---|---|
defineAgent() | configured agent_loop or persona | Both bind a model, instructions, tools, skills, and an execution environment. |
| Agent instance | session | Both preserve one continuing conversation identity. |
defineWorkflow() | workflow or pipeline | Both describe finite work; Harn uses a typed stage graph when the graph must be inspectable. |
| Durable event stream | transcript plus EventLog | Both retain replayable runtime events. Harn also uses the EventLog for deterministic effect replay. |
@flue/react hooks | Harn Apps host plus MCP Apps UI resource | Flue projects durable state into React hooks. Harn serves host-neutral app resources and lets each host own native presentation. |
| Virtual, local, or remote sandbox | Harn sandbox and host capabilities | Both keep conversation persistence separate from workspace lifetime and access policy. |
| Target | host or deployment adapter | Flue targets Node.js and Cloudflare. A Harn program runs through CLI, IDE, protocol, self-hosted, or cloud adapters. |
Start with Flue's agent guide, workflow guide, event reference, and React guide when comparing a specific developer path.
Inngest
| Inngest term | Harn equivalent | Notes |
|---|---|---|
Function | pipeline | Both are the durable unit. |
Run | session, run_id | Direct match. |
step.run(key, ...) | step.run(key, input?, handler, options?) | Harn memoizes completed step results in the EventLog and replays matching steps without re-invoking the handler. |
step.sleep / step.waitForEvent | agent_await_resumption + resume_when | Conceptually equivalent. |
Event | trigger event, agent event | Direct match. |
| Step replay | step.run + session resume + worker snapshot | Harn supports both replay-from-top memoized steps and checkpoint/snapshot resume. |
If you arrive from Inngest expecting step.run-style memoized replay, start
with Durable step stdlib. Durable timers and event waits
remain separate primitives: use agent_await_resumption and resume_when for
long waits.
Mastra
| Mastra term | Harn equivalent | Notes |
|---|---|---|
Agent | agent_loop invocation | Direct match. |
Workflow | workflow | Direct match. |
Thread (per-conversation) | session_id | Mastra's thread is Harn's session. |
Resource (per-user/entity) | partial — tenant_id covers some of it | Mastra splits per-user vs per-conversation; Harn collapses to session + tenant. |
working memory / semantic recall | memory builtins | Conceptually similar, less typed. |
ACP — Agent Client Protocol
ACP is the most important map for anyone using Harn's serve adapter, because
we speak ACP natively.
| ACP term | Harn equivalent | Notes |
|---|---|---|
session/new, session/load, session/resume | agent_session_open, session fork, snapshot resume | Direct match. |
session/prompt | one user message → agent_loop invocation | Direct match. |
prompt_turn | one agent_loop invocation | The outer user-message → final-response cycle, terminated by a typed terminal outcome and lossless stop_reason. One invocation contains many iterations. |
stop_reason | stop_reason | Same names. |
available_commands | skills, tool registry | Partial match; ACP advertises slash-style commands. |
Plan (agent plan updates) | task_ledger, progress tool | Direct match. |
tool_call | tool call | Same names. |
session/cancel | close_agent, cancellation token | Direct match. |
session/request_permission | approval_policy, permissions | Direct match. |
Read this carefully if you're writing ACP integrations: ACP's prompt_turn
is the outer concept (one user request → final response with stop reason).
Harn's loop counts iterations, which are model round-trips inside the prompt
turn — the transcript events fire as iteration_start / iteration_end, and
the steering seams use the same names. One agent_loop(...) invocation maps
to one ACP prompt_turn and contains many iteration_* events.
A2A — Agent2Agent Protocol
| A2A term | Harn equivalent | Notes |
|---|---|---|
Task | worker, agent_loop invocation | A2A's Task is one unit of work with lifecycle state and history. |
Message | transcript event, message | Direct match. |
TaskState (submitted, working, input-required, completed, ...) | final_status, suspended states | A2A's state machine is more explicit; Harn maps closely. |
Part (TextPart, FilePart, DataPart) | block | Direct match. |
Artifact | artifact | Same name. |
MCP — Model Context Protocol
MCP deliberately avoids conversation-shape vocabulary. It defines Tool,
Resource, Prompt, Sampling, Elicitation — primitives on which
conversations run, not the conversations themselves.
| MCP term | Harn equivalent | Notes |
|---|---|---|
sampling/createMessage | llm_call | One model call. |
Tool | tool | Same shape. |
Resource | hostlib resource, transcript asset | Same shape. |
Prompt | prompt template, prompt library | Same shape. |
Elicitation | HITL hitl.ask | Server-initiated pause-and-ask pattern. |
MCP has no turn / session / agent_loop — those are above MCP's layer. Use
MCP as your tool surface, not as your orchestration model.
AG-UI
AG-UI is event-based UI streaming, not loop topology. Its vocabulary (Lifecycle Events, Text Message Events, Tool Call Events, State Management Events)
maps onto Harn's transcript event categories with different names but the same
shapes. Harn's serve adapter emits AG-UI-compatible events.