Skip to main content

Documentation Index

Fetch the complete documentation index at: https://docs.profclaw.ai/llms.txt

Use this file to discover all available pages before exploring further.

Agent sessions represent a single autonomous execution run - from receiving a task to completing it. Sessions are created implicitly when agentic chat is started, but you can also inspect and manage them directly.

​
Session Lifecycle

created -> queued -> running -> completed | failed | cancelled
A session maps to a Task in the queue, an agentic SSE stream in the chat API, and an audit log of all tool calls made during execution.

​
Starting a Session

The primary way to start an agentic session is through the chat API: 
curl -X POST http://localhost:3000/api/chat/conversations/conv_01/messages/agentic \
  -H "Content-Type: application/json" \
  --cookie "profclaw_session=<token>" \
  -d '{
    "content": "Add unit tests for the auth module",
    "model": "claude-sonnet-4-6",
    "effort": "high",
    "maxSteps": 50
  }'
This returns an SSE stream. See Chat Stream for the full event reference.

​
Session Configuration

ParameterTypeDefaultDescription
effortstringmediumlow | medium | high | max - controls step budget
maxStepsnumberVariesHard cap on autonomous steps (1-200)
maxBudgetnumberNoneToken budget for the session
showThinkingbooleantrueStream reasoning blocks
securityModestringfullTool permission mode for agentic runs
Agentic mode always uses securityMode: full - all tools are pre-approved. For interactive approval, use the with-tools endpoint instead.

​
Session Timeout

Sessions have a hard timeout of 3 minutes. When reached, an error SSE event is sent with code: "TIMEOUT" and the stream closes. Long-running tasks should be broken into smaller steps.

​
Viewing Session History

Each agentic session saves tool calls and the final summary as a conversation message. Retrieve them via: 
GET /api/chat/conversations/:id
The assistantMessage in the response includes toolCalls with each tool call, its arguments, result, and status: "success" | "error".

​
Memory Session Integration

Agentic sessions optionally link to a memory session for context persistence: 
POST /api/memory/sessions

{
  "name": "auth-refactor session",
  "conversationId": "conv_01"
}
Call POST /api/memory/warm before starting an agentic session to pre-load relevant memory into context.

​
Execution Engine

Under the hood, streamAgenticChat() from src/chat/index.ts drives the agentic loop:
  1. Builds system prompt with agentMode: true (appends AGENT_MODE_SUFFIX)
  2. Calls the AI model with all available tools
  3. Executes each tool call via the ChatToolHandler
  4. Repeats until the model stops calling tools or maxSteps is reached
  5. Emits typed SSE events at each step for real-time UI updates
The tool handler uses securityMode: full in agentic mode, meaning all tools execute without approval prompts. This matches the behavior of autonomous agent runners like Claude Code.