{
  "meta": {
    "upstreamModel": "moonshotai/kimi-k2.5-0127",
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    "workspaceTokenized": true,
    "scenario": "sub-agents",
    "seq": 2,
    "recordedAt": "2026-06-11T01:05:12.799Z"
  },
  "request": {
    "model": "moonshotai/kimi-k2.5",
    "messages": [
      {
        "role": "system",
        "content": "# VeilCLI Agent Runtime\n\nYou are an autonomous AI agent running inside VeilCLI v1.10.0.\n\n- You are an agent named **orchestrator**\n- You operate in **chat** mode\n- Your session ID is `sess_de4a640b567efbf4`\n\n\n---\n\n# Environment\n\n- **OS:** Linux 5.11.0-46-generic\n- **Shell:** /bin/bash\n- **Working Directory:** `<WORKSPACE>`\n- **Date:** 2026-06-11\n- **Node.js:** v20.20.2\n\n## Available MCP Servers\nNone configured\n\n\n---\n\n## Agent Instructions\n\n# Orchestrator\n\nYou are Orchestrator. You delegate work to sub-agents with your tools and report their results back to the user. Follow the user's delegation instructions exactly. Keep your own replies short."
      },
      {
        "role": "user",
        "content": "Spawn two sub-agents using agent_spawn, both with agent \"worker\": one with instance_name \"poet\" and objective \"write short poems\", one with instance_name \"mathematician\" and objective \"do precise arithmetic\". Then use agent_message to ask poet for a two-line poem about the sea, and ask mathematician what 7 multiplied by 6 equals. After you have BOTH answers, write a final message to me that contains both, clearly labeled POEM and MATH. Do not end your turn without that summary."
      },
      {
        "role": "assistant",
        "content": "I'll spawn both agents and then send them their respective questions.",
        "tool_calls": [
          {
            "id": "agent_spawn_0",
            "type": "function",
            "function": {
              "name": "agent_spawn",
              "arguments": "{\"agent\": \"worker\", \"instance_name\": \"poet\", \"objective\": \"write short poems\"}"
            }
          },
          {
            "id": "agent_spawn_1",
            "type": "function",
            "function": {
              "name": "agent_spawn",
              "arguments": "{\"agent\": \"worker\", \"instance_name\": \"mathematician\", \"objective\": \"do precise arithmetic\"}"
            }
          }
        ]
      },
      {
        "role": "tool",
        "tool_call_id": "agent_spawn_0",
        "content": "<instance-name>poet</instance-name>\n<session-id>sess_795d52f03cdfc24d</session-id>"
      },
      {
        "role": "tool",
        "tool_call_id": "agent_spawn_1",
        "content": "<instance-name>mathematician</instance-name>\n<session-id>sess_8a71735370b7ea6e</session-id>"
      }
    ],
    "tools": [
      {
        "type": "function",
        "function": {
          "name": "agent_control",
          "description": "Inspect, update, or stop a subagent session. Actions: get-state (cheap; returns isIdle, message/tool counts since your last contact, instance_name); get-summary (paid LLM call; natural-language summary of recent activity, rate-limited); stop (cooperative cancel, dangling-tool cleanup); update-session (set per-session reasoning/budget on the session row — applied immediately for budget_override; applied on the next turn for reasoning); get-last-message (read the last assistant message text, or the last-turn full-steps log when params.full_steps=true). Optional params object carries action-specific args.",
          "parameters": {
            "type": "object",
            "properties": {
              "sessionId": {
                "type": "string",
                "description": "Session ID of the subagent to inspect / update / cancel."
              },
              "action": {
                "type": "string",
                "enum": [
                  "get-state",
                  "get-summary",
                  "stop",
                  "update-session",
                  "get-last-message"
                ],
                "description": "Operation to perform."
              },
              "params": {
                "type": "object",
                "description": "Action-specific arguments. update-session: { reasoning?: { effort: none|auto|minimal|low|medium|high|xhigh|max|<custom>, max_tokens?: int }, budget_override?: { max_tokens?, max_wall_seconds?, max_spawn_depth? } }. get-last-message: { full_steps?: boolean }. Other actions: leave empty."
              }
            },
            "required": [
              "sessionId",
              "action"
            ]
          }
        }
      },
      {
        "type": "function",
        "function": {
          "name": "agent_message",
          "description": "Send a message to a specific subagent session. Synchronous by default — blocks until the subagent replies. Pass `async_inform: true` for fire-and-forget delivery: the call returns a fixed notice immediately and the subagent's response is later delivered to your session as a new user message. IMPORTANT: a SECOND `async_inform: true` to a target whose dispatch is already in flight returns the FIRST mid-run response (NOT the final response). The dispatcher's final reply is delivered only to the FIRST (seed) async_inform message of the chain. Subsequent callers to a busy target also receive only their own mid-run reply, not the dispatcher's final reply. Target agent is derived from the session row; the `agent` param has been removed (Phase 3).",
          "parameters": {
            "type": "object",
            "properties": {
              "sessionId": {
                "type": "string",
                "description": "Session ID of the target subagent (from agent_spawn)."
              },
              "message": {
                "type": "string",
                "description": "Message to send."
              },
              "async_inform": {
                "type": "boolean",
                "description": "When true, return a static notice immediately and dispatch the turn in the background. End your turn after receiving the notice. A SECOND async_inform to a target with an in-flight dispatch returns the FIRST mid-run text response, NOT the final response."
              },
              "timeout": {
                "type": "integer",
                "minimum": 1,
                "description": "Sync-mode timeout in seconds (default: 600 = 10 minutes). Ignored when async_inform=true (async has no default timeout — use agent_control({action:\"stop\"}) to cancel)."
              },
              "full_steps": {
                "type": "boolean",
                "description": "Instead of receiving the last response, When \"full_steps\" is true all assistant text responses containing a per-line log of all assistant tool calls are going to be received with the final response. When this message is a FOLLOW-UP (msg 2+, sent while a prior dispatch is still running), full_steps is silently IGNORED — Default: false."
              }
            },
            "required": [
              "sessionId",
              "message"
            ]
          }
        }
      },
      {
        "type": "function",
        "function": {
          "name": "agent_spawn",
          "description": "Start a new session with a subagent. Required: agent (name), instance_name (caller-unique label), objective (what the subagent should accomplish). Optional: success_criteria (guideline injected into system prompt), overrides (per-spawn LLM config: { reasoning: { effort, max_tokens? } }), initial_message (object with `message` and optional `async_inform:true` to dispatch the first turn in the background). Returns `{ instance_name, sessionId }` (no initial_message), `{ instance_name, sessionId, content }` (sync), or `{ instance_name, sessionId, notice }` (async).",
          "parameters": {
            "type": "object",
            "properties": {
              "agent": {
                "type": "string",
                "description": "Name of the agent to spawn."
              },
              "instance_name": {
                "type": "string",
                "description": "Unique label for this subagent under the caller (lets you address it by name)."
              },
              "objective": {
                "type": "string",
                "description": "What this subagent should accomplish; injected into its system prompt."
              },
              "success_criteria": {
                "type": "string",
                "description": "Optional completion guideline; injected into system prompt below the objective."
              },
              "overrides": {
                "type": "object",
                "description": "Optional LLM overrides for the spawned session. Sets the spawn's session-level values; per-call overrides on later turns still take precedence. Resolution: per-call > session > agent default.",
                "additionalProperties": false,
                "properties": {
                  "reasoning": {
                    "type": "object",
                    "additionalProperties": false,
                    "properties": {
                      "effort": {
                        "type": "string",
                        "description": "Engine-blind reasoning effort: none | auto | minimal | low | medium | high | xhigh | max | <custom string for niche providers>."
                      },
                      "max_tokens": {
                        "type": "integer",
                        "minimum": 1,
                        "description": "Optional cap on reasoning tokens. Maps to claude-cli SDK thinking.budgetTokens; sent as body.reasoning.max_tokens to openai providers that accept it."
                      }
                    },
                    "required": [
                      "effort"
                    ]
                  }
                }
              },
              "initial_message": {
                "type": "object",
                "description": "Optional first message. If absent, session is created with no LLM turn (zero tokens).",
                "properties": {
                  "message": {
                    "type": "string",
                    "description": "First message to send to the spawned subagent."
                  },
                  "async_inform": {
                    "type": "boolean",
                    "description": "When true, dispatch the first turn in the background and return a static notice immediately. End your turn after receiving the notice."
                  }
                },
                "required": [
                  "message"
                ]
              }
            },
            "required": [
              "agent",
              "instance_name",
              "objective"
            ]
          }
        }
      },
      {
        "type": "function",
        "function": {
          "name": "task_spawn",
          "description": "Spawn a sub-agent task with an isolated context. Sync (wait:true, default) or async (wait:false for parallel fan-out). Returns task result or taskId.",
          "parameters": {
            "type": "object",
            "properties": {
              "agent": {
                "type": "string",
                "description": "Name of the agent to spawn a task for"
              },
              "instruction": {
                "type": "string",
                "description": "Instruction for the sub-agent. Use \"/skill-name args\" to trigger a skill."
              },
              "returnMode": {
                "type": "string",
                "enum": [
                  "summary",
                  "raw",
                  "lastMessage"
                ],
                "description": "How to return results (default: summary)"
              },
              "wait": {
                "type": "boolean",
                "description": "true=sync (wait for result), false=async (returns taskId immediately). Default: true"
              }
            },
            "required": [
              "agent",
              "instruction"
            ]
          }
        }
      },
      {
        "type": "function",
        "function": {
          "name": "task_status",
          "description": "Check the status and output of a task.",
          "parameters": {
            "type": "object",
            "properties": {
              "taskId": {
                "type": "string",
                "description": "Task ID to check"
              }
            },
            "required": [
              "taskId"
            ]
          }
        }
      }
    ],
    "temperature": 0.1,
    "reasoning": {
      "effort": "low"
    }
  },
  "response": {
    "model": "moonshotai/kimi-k2.5-0127",
    "choices": [
      {
        "index": 0,
        "message": {
          "role": "assistant",
          "content": "Now I'll send both agents their questions in parallel:",
          "reasoning": "Both agents are spawned. Now I need to send messages to both:\n1. Ask \"poet\" (sess_795d52f03cdfc24d) for a two-line poem about the sea\n2. Ask \"mathematician\" (sess_8a71735370b7ea6e) what 7 multiplied by 6 equals\n\nThese can be done in parallel since they're independent.",
          "tool_calls": [
            {
              "id": "agent_message_2",
              "type": "function",
              "function": {
                "name": "agent_message",
                "arguments": "{\"sessionId\":\"sess_795d52f03cdfc24d\",\"message\":\"Write a two-line poem about the sea.\"}"
              }
            },
            {
              "id": "agent_message_3",
              "type": "function",
              "function": {
                "name": "agent_message",
                "arguments": "{\"sessionId\":\"sess_8a71735370b7ea6e\",\"message\":\"What does 7 multiplied by 6 equal?\"}"
              }
            }
          ]
        },
        "finish_reason": "tool_calls"
      }
    ],
    "usage": {
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