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refactor: rename clawdbot to moltbot with legacy compat

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Peter Steinberger
2026-01-27 12:19:58 +00:00
parent 83460df96f
commit 6d16a658e5
1839 changed files with 11250 additions and 11199 deletions
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10
docs/concepts/agent-loop.md
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@@ -3,13 +3,13 @@ summary: "Agent loop lifecycle, streams, and wait semantics"
read_when:
- You need an exact walkthrough of the agent loop or lifecycle events
---
# Agent Loop (Clawdbot)
# Agent Loop (Moltbot)
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 Clawdbot, a loop is a single, serialized run per session that emits lifecycle and stream events
In Moltbot, 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.
@@ -30,7 +30,7 @@ wired end-to-end.
- subscribes to pi events and streams assistant/tool deltas
- enforces timeout -> aborts run if exceeded
- returns payloads + usage metadata
4) `subscribeEmbeddedPiSession` bridges pi-agent-core events to Clawdbot `agent` stream:
4) `subscribeEmbeddedPiSession` bridges pi-agent-core events to Moltbot `agent` stream:
- tool events => `stream: "tool"`
- assistant deltas => `stream: "assistant"`
- lifecycle events => `stream: "lifecycle"` (`phase: "start" | "end" | "error"`)
@@ -51,12 +51,12 @@ wired end-to-end.
- A session write lock is acquired; `SessionManager` is opened and prepared before streaming.
## Prompt assembly + system prompt
- System prompt is built from Clawdbot’s base prompt, skills prompt, bootstrap context, and per-run overrides.
- System prompt is built from Moltbot’s base prompt, skills prompt, bootstrap context, and per-run overrides.
- Model-specific limits and compaction reserve tokens are enforced.
- See [System prompt](/concepts/system-prompt) for what the model sees.
## Hook points (where you can intercept)
Clawdbot has two hook systems:
Moltbot 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.