f58b031465
A reviewer found that window 2 (a cancel from a synchronous agent/status('running')
listener) had the same early-whenIdle() race that window 1 already guards: it
unconditionally `setStatus('idle')` + continue, which settles `whenIdle()`
waiters — so if the running listener cancels AND queues replacement work, the
waiter resolves while the replacement is still queued-and-unrun (the next
iteration runs it later, but the caller already observed quiescence).
Mirror window 1: after clearing the marker, only `setStatus('idle')` when
nothing new is queued; otherwise fall through to run the queued replacement
(status is already `running`), so `whenIdle()` resolves on that turn's
running→idle. Regression test reproduces the reviewer's interleaving (running
listener cancels A, sends B; whenIdle() resolves only after B ran).
Also syncs the cancellation contract in the two ACP RFCs that describe the live
behavior: `session/cancel` is the queue-aware `agent.cancel()` (drops an
about-to-start turn), not the old best-effort `agent.abort()` pre-step
limitation.
dsh-agent-loop
THE concrete agent plugin: ReactLoopAgent and the loop driver. Implements the Agent interface and drives the session/turn/step lifecycle.
This is the only package in the harness that contains concrete loop logic. Everything else is an abstract service or a plugin against extension seams — new behavior goes into plugins, not here.
Service: AgentLoop (ctx key: agentLoop)
Public API
ctx.agentLoop.create(id: string, options?: AgentOptions): ReactLoopAgent— config-driven create: an agent on a fresh per-run session id${id}-session-<uuid>(no cwd). Used forcordis.yml-configured agents. The per-run uuid avoids colliding with the on-disk log a prior run materialized once a durable persistence backend is loaded; each run is a new session (a deliberate demo simplification — a real resume-or-create policy is a TODO). Disposed with the calling fiber.
AgentLoop also implements the AgentFactory seam and registers itself via ctx.agents.setFactory(this), so plugins create/resume agents through ctx.agents (the interface):
ctx.agents.create({ agentId, sessionId, meta?, agentOptions? })— programmatic create on a caller-suppliedsessionId(e.g. an ACP-generated id), NOT${id}-session.ctx.agents.resume({ agentId, resumeSessionId, agentOptions? })— load a persisted session viactx.sessionPersistence(session persistence) and resume an agent on it. The live session id is the resumed id; turn numbering and derived history continue from the loaded log. Requires a session-persistence backend (NOT hard-injected — non-persistent demos still work;resumerejects with a clear error when persistence is absent).
Injected services
agents, sessions, llm, tools, systemPrompt — all five interface services.
Configuration (schemastery)
interface Config {
agents: Array<{
id: string // required
model?: string
systemPrompt?: string
}>
}
Agents listed in config are auto-created at startup.
Classes
ReactLoopAgent— the concreteAgentimplementation. Owns the inbox (Inbox), the per-stepAbortController, and the loop driver. Everything observable happens through session events and theagent/*event taxonomy.Inbox— per-agent queued + steering FIFOs (enqueue,steer,drainQueued,drainSteering,waitForQueued).
Loop lifecycle (loop.ts)
One invocation of runLoop() drives one agent for its whole lifetime:
forever:
wait for queued messages (idle)
TURN (error-contained):
drain queued → 'turn/start' → session('user/message')
STEP loop:
drain steering
assembly = systemPrompt.assemble()
request = waterfall agent/request
stream llm.stream(request) → session('assistant/chunk')
message = waterfall agent/step-result
session('assistant/message')
each tool-call: session('tool/call') → tools.execute() → session('tool/result')
drain steering → session('steering/message')
cont = waterfall agent/turn-continuation
if !cont: break
session('turn/end')
await session/flush
re-enqueue leftover steering as queued
idle unless more queued
Error containment: a throwing plugin ends the turn, never the loop. Dispose mid-turn emits agent/status('disposed') and ends with reason disposed. A step that hits the model's output-token ceiling makes the turn end max-tokens (the rule: any max-tokens step in the turn surfaces as max-tokens; disposed/aborted/error still take precedence) — distinct from a clean completed stop.
Cancellation: agent.abort() aborts only the in-flight step; agent.cancel() is the broad verb — it clears the queued + steering FIFOs, aborts the in-flight step, and drives a turn-scoped marker the driver checks at every point a turn could start or continue (right after the idle wait, after the running flip, before each step, and at the continuation gate) so a turn about to start is dropped. A cancelled turn ends aborted; a queued-but-not-started prompt never runs and cannot be batched into the cancelled turn. The marker is reset once per loop iteration, so a cancel governs exactly one turn and never leaks onto a later prompt.
What is NOT here
Everything that goes beyond "call the model, run the tools, repeat" belongs to plugins listening on the event taxonomy:
- Hooks:
agent/request,agent/step-result,tools/execute,agent/turn-continuation - Compaction:
agent/request - Sandbox, permission, plan mode:
tools/execute - Sub-agents: TODO seam on
AgentLoop.create() - Persistence:
session/event+session/flush - UI:
agent/stream-chunk+agent/*events