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QueryEngine.ts is the SDK/headless mode lifecycle engine. While REPL.tsx drives interactive terminal sessions with React/Ink, QueryEngine.ts exposes the same agent loop as a clean programmatic API: submitMessage(prompt) returns an AsyncGenerator<SDKMessage> that streams results back to the consumer.
QueryEngine.ts is ~1,295 lines and orchestrates the entire lifecycle from prompt ingestion through system prompt assembly, slash command parsing, agent loop execution, and JSONL persistence.

​
submitMessage Interface

// src/QueryEngine.ts
async *submitMessage(
  prompt: string | ContentBlockParam[],
  options?: {
    sessionId?: string
    permissionMode?: PermissionMode
    // ...
  }
): AsyncGenerator<SDKMessage> {
  // 1. fetchSystemPromptParts()  — assemble system prompt
  // 2. processUserInput()        — handle /commands
  // 3. query()                   — main agent loop
  // 4. yield SDKMessage          — stream to consumer
}
The generator yields SDKMessage values incrementally as the agent loop progresses. Consumers can for await over it to receive streaming output.

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Internal Flow

submitMessage(prompt)
      │
      ▼
fetchSystemPromptParts()       ← tools → prompt sections, CLAUDE.md memory
      │
      ▼
processUserInput()             ← parse /commands, build UserMessage
      │
      ▼
recordTranscript()             ← persist user message to disk (JSONL)
      │
      ▼
┌─→ normalizeMessagesForAPI()  ← strip UI-only fields, compact if needed
│   │
│   ▼
│   Claude API (streaming)     ← POST /v1/messages with tools + system prompt
│   │
│   ▼
│   stream events              ← message_start → content_block_delta → message_stop
│   │
│   ├─ text block ──────────── → yield SDKMessage to consumer
│   │
│   └─ tool_use block?
│       │
│       ▼
│   StreamingToolExecutor      ← partition: concurrent-safe vs serial
│       │
│       ▼
│   canUseTool()               ← permission check (hooks + rules + UI prompt)
│       │
│       ├─ DENY ─────────────→ append tool_result(error), continue loop
│       │
│       └─ ALLOW
│           │
│           ▼
│       tool.call()            ← execute the tool (Bash, Read, Edit, etc.)
│           │
│           ▼
│       append tool_result     ← push to messages[], recordTranscript()
│           │
└─────────┘                   ← loop back to API call
      │
      ▼  (stop_reason != "tool_use")
yield result SDKMessage        ← final text, usage, cost, session_id

​
StreamingToolExecutor

StreamingToolExecutor (in src/services/tools/StreamingToolExecutor.ts) manages concurrent tool execution within a single agent turn. It partitions the tools requested by the model into two buckets:
  • Concurrent-safe tools — isReadOnly() or otherwise side-effect-free; run in parallel
  • Serial tools — write operations like FileEditTool, BashTool; run sequentially to avoid conflicts
tool_use blocks from API response
        │
        ▼
StreamingToolExecutor.partition()
        │
   ┌────┴────┐
   ▼         ▼
parallel   serial
 tools      tools
   │           │
   └────┬──────┘
        ▼
  await all results
        │
        ▼
   tool_results[] → appended to messages[]

​
autoCompact()

autoCompact() triggers when the accumulated token count in messages[] exceeds the configured threshold. It:
  1. Calls getMessagesAfterCompactBoundary() to split history into old and recent
  2. Sends the older messages to a separate Claude API call for summarization
  3. Replaces them with [summary] + [compact_boundary] + [recent messages]
The compact boundary is persisted in the JSONL session log as a system/compact_boundary entry, so it survives session resume.

​
runTools()

runTools() handles tool orchestration after StreamingToolExecutor returns results. It:
  • Appends each tool_result block to messages[]
  • Calls recordTranscript() for each result (fire-and-forget for assistant messages)
  • Handles SDKPermissionDenial for denied tools
  • Detects the SYNTHETIC_OUTPUT_TOOL_NAME sentinel for structured output

​
SDKMessage Types

submitMessage yields five distinct message shapes, all discriminated by type: 
// src/entrypoints/agentSdkTypes.ts

// Replays the original user message at the start of the stream
type SDKUserMessageReplay = {
  type: 'user'
  message: MessageParam
}

// Emitted when a tool call is denied by the permission system
type SDKPermissionDenial = {
  type: 'permission_denial'
  tool: string
  reason: string
}

// Marks a context compaction boundary in the stream
type SDKCompactBoundaryMessage = {
  type: 'compact_boundary'
  summary: string
}

// Streaming status updates (progress, thinking, etc.)
type SDKStatus = {
  type: 'status'
  value: string
}

// Final result message with usage and cost info
type SDKMessage =
  | SDKUserMessageReplay
  | SDKPermissionDenial
  | SDKCompactBoundaryMessage
  | SDKStatus
  | AssistantMessage  // final text content

​
AsyncGenerator Streaming Chain

The streaming chain is end-to-end: the Claude API streams content_block_delta events, query.ts yields them as SDKMessage values, and QueryEngine.ts re-yields them to the consumer. No buffering occurs at the engine layer. 
Claude API (SSE)
     │  content_block_delta events
     ▼
query() in query.ts
     │  yield SDKMessage
     ▼
submitMessage() in QueryEngine.ts
     │  yield SDKMessage
     ▼
Consumer (for await ... of submitMessage())

​
Using QueryEngine in Headless/SDK Mode

import { QueryEngine } from '@anthropic-ai/claude-code'

const engine = new QueryEngine({
  permissionMode: 'default',
  // ...options
})

for await (const message of engine.submitMessage('Refactor this function')) {
  if (message.type === 'status') {
    process.stdout.write(message.value)
  } else if (message.type === 'assistant') {
    console.log(message.content)
  } else if (message.type === 'permission_denial') {
    console.warn(`Tool denied: ${message.tool} — ${message.reason}`)
  }
}
In headless/SDK mode there is no interactive permission prompt. Tool permission decisions are driven entirely by the permissionMode option and any alwaysAllow/alwaysDeny rules configured in settings.json.

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