Skip to main contentAgent Loop (Clawdia)
An agentic loop is the full “real” run of an agent: intake → context assembly → model inference →
tool execution → streaming replies → persistence. It’s the authoritative path that turns a message
into actions and a final reply, while keeping session state consistent.
In Clawdia, a loop is a single, serialized run per session that emits lifecycle and stream events
as the model thinks, calls tools, and streams output. This doc explains how that authentic loop is
wired end-to-end.
Entry points
- Gateway RPC:
agent and agent.wait.
- CLI:
agent command.
How it works (high-level)
agent RPC validates params, resolves session (sessionKey/sessionId), persists session metadata, returns { runId, acceptedAt } immediately.
agentCommand runs the agent:
- resolves model + thinking/verbose defaults
- loads skills snapshot
- calls
runEmbeddedPiAgent (pi-agent-core runtime)
- emits lifecycle end/error if the embedded loop does not emit one
runEmbeddedPiAgent:
- serializes runs via per-session + global queues
- resolves model + auth profile and builds the pi session
- subscribes to pi events and streams assistant/tool deltas
- enforces timeout -> aborts run if exceeded
- returns payloads + usage metadata
subscribeEmbeddedPiSession bridges pi-agent-core events to Clawdia agent stream:
- tool events =>
stream: "tool"
- assistant deltas =>
stream: "assistant"
- lifecycle events =>
stream: "lifecycle" (phase: "start" | "end" | "error")
agent.wait uses waitForAgentJob:
- waits for lifecycle end/error for
runId
- returns
{ status: ok|error|timeout, startedAt, endedAt, error? }
Queueing + concurrency
- Runs are serialized per session key (session lane) and optionally through a global lane.
- This prevents tool/session races and keeps session history consistent.
- Messaging channels can choose queue modes (collect/steer/followup) that feed this lane system.
See Command Queue.
Session + workspace preparation
- Workspace is resolved and created; sandboxed runs may redirect to a sandbox workspace root.
- Skills are loaded (or reused from a snapshot) and injected into env and prompt.
- Bootstrap/context files are resolved and injected into the system prompt report.
- A session write lock is acquired;
SessionManager is opened and prepared before streaming.
Prompt assembly + system prompt
- System prompt is built from Clawdia’s base prompt, skills prompt, bootstrap context, and per-run overrides.
- Model-specific limits and compaction reserve tokens are enforced.
- See System prompt for what the model sees.
Hook points (where you can intercept)
Clawdia has two hook systems:
- Internal hooks (Gateway hooks): event-driven scripts for commands and lifecycle events.
- Plugin hooks: extension points inside the agent/tool lifecycle and gateway pipeline.
Internal hooks (Gateway hooks)
agent:bootstrap: runs while building bootstrap files before the system prompt is finalized.
Use this to add/remove bootstrap context files.
- Command hooks:
/new, /reset, /stop, and other command events (see Hooks doc).
See Hooks for setup and examples.
Plugin hooks (agent + gateway lifecycle)
These run inside the agent loop or gateway pipeline:
before_agent_start: inject context or override system prompt before the run starts.
agent_end: inspect the final message list and run metadata after completion.
before_compaction / after_compaction: observe or annotate compaction cycles.
before_tool_call / after_tool_call: intercept tool params/results.
tool_result_persist: synchronously transform tool results before they are written to the session transcript.
message_received / message_sending / message_sent: inbound + outbound message hooks.
session_start / session_end: session lifecycle boundaries.
gateway_start / gateway_stop: gateway lifecycle events.
See Plugins for the hook API and registration details.
Streaming + partial replies
- Assistant deltas are streamed from pi-agent-core and emitted as
assistant events.
- Block streaming can emit partial replies either on
text_end or message_end.
- Reasoning streaming can be emitted as a separate stream or as block replies.
- See Streaming for chunking and block reply behavior.
- Tool start/update/end events are emitted on the
tool stream.
- Tool results are sanitized for size and image payloads before logging/emitting.
- Messaging tool sends are tracked to suppress duplicate assistant confirmations.
Reply shaping + suppression
- Final payloads are assembled from:
- assistant text (and optional reasoning)
- inline tool summaries (when verbose + allowed)
- assistant error text when the model errors
NO_REPLY is treated as a silent token and filtered from outgoing payloads.
- Messaging tool duplicates are removed from the final payload list.
- If no renderable payloads remain and a tool errored, a fallback tool error reply is emitted
(unless a messaging tool already sent a user-visible reply).
Compaction + retries
- Auto-compaction emits
compaction stream events and can trigger a retry.
- On retry, in-memory buffers and tool summaries are reset to avoid duplicate output.
- See Compaction for the compaction pipeline.
Event streams (today)
lifecycle: emitted by subscribeEmbeddedPiSession (and as a fallback by agentCommand)
assistant: streamed deltas from pi-agent-core
tool: streamed tool events from pi-agent-core
Chat channel handling
- Assistant deltas are buffered into chat
delta messages.
- A chat
final is emitted on lifecycle end/error.
Timeouts
agent.wait default: 30s (just the wait). timeoutMs param overrides.
- Agent runtime:
agents.defaults.timeoutSeconds default 600s; enforced in runEmbeddedPiAgent abort timer.
Where things can end early
- Agent timeout (abort)
- AbortSignal (cancel)
- Gateway disconnect or RPC timeout
agent.wait timeout (wait-only, does not stop agent)