Claude Platform Docs

List Session Threads

$ ant beta:sessions:threads list
GET/v1/sessions/{session_id}/threads

List Session Threads

Parameters
--session-id: string⁠Path parameter
--limit: optional number⁠Query parameter

Maximum results per page. Defaults to 1000.

formatint32
--page: optional string⁠Query parameter

Opaque pagination cursor from a previous response's next_page. Forward-only.

--status: optional array of BetaManagedAgentsSessionThreadStatus⁠Query parameter

Return only threads that have one of these statuses.

Repeat the parameter to give more than one status. Leave it out to return threads of every status.

--beta: optional array of AnthropicBeta⁠Header parameter

Optional header to specify the beta version(s) you want to use.

--workspace-id: optional string⁠Header parameter

Optional header to select the Workspace for this request. The value is a Workspace ID (for example, wrkspc_011CZkZaBF1tNoB5wlCeusgy).

Only needed for credentials that can act on more than one Workspace. A credential that belongs to a specific Workspace may omit it; if sent, it must match that Workspace.

Returns
BetaManagedAgentsListSessionThreads: object{ data, next_page }

Paginated list of threads within a session.

data: optional array of BetaManagedAgentsSessionThread { type: "session_thread", id, agent, 9 more }

Threads in the session, primary first then children in spawn order.

type: "session_thread"
id: string

Unique identifier for this thread.

agent: BetaManagedAgentsSessionThreadAgent or BetaManagedAgentsAdvisor or BetaManagedAgentsInlineAgent

Resolved agent definition for this thread. Snapshot of the agent at thread creation time.

One of the following:
beta_managed_agents_session_thread_agent: object{ type: "agent", id, description, 7 more }

Resolved agent definition for a single session_thread. Snapshot of the agent at thread creation time. The multiagent roster is not repeated here; read it from Session.agent.

beta_managed_agents_advisor: object{ type: "advisor", model }

Platform advisor roster entry: a model the session's primary thread may consult mid-turn.

type: "advisor"
model: string

The advisor model id.

beta_managed_agents_inline_agent: object{ type: "inline", description, mcp_servers, 5 more }

An agent that has no Agent resource, and so no id or version. It is defined inline, in a workflow run's plan or when a session thread is spawned, and is not saved.

archived_at: string

When the thread was archived. Null if not archived.

formatdate-time
created_at: string

When the thread was created.

formatdate-time
parent_thread_id: string

Parent thread that spawned this thread. Null for the primary thread.

session_id: string

The session this thread belongs to.

stats: object{ active_seconds, duration_seconds, startup_seconds }

Timing statistics for this thread. Null until the thread's first status transition.

active_seconds: optional number

Cumulative time in seconds the thread spent actively running. Excludes idle time.

formatdouble
duration_seconds: optional number

Elapsed time since thread creation in seconds. For archived threads, frozen at the final update.

formatdouble
startup_seconds: optional number

Time in seconds for the thread to begin running. Zero for child threads, which start immediately.

formatdouble
status: "running" or "idle" or "rescheduling" or "terminated"

Current execution status of the thread.

One of the following:
"running"
"idle"
"rescheduling"
"terminated"
updated_at: string

When the thread was last updated.

formatdate-time
usage: object{ active_seconds, cache_creation, cache_read_input_tokens, 4 more }

Cumulative token usage for this thread. Null until the thread's first idle transition.

active_seconds: optional number

Cumulative time in seconds this thread spent in running status. Equal to stats.active_seconds; surfaced here so a thread's usage carries every quantity its cost is priced on.

formatdouble
cache_creation: optional object{ ephemeral_1h_input_tokens, ephemeral_5m_input_tokens }

Tokens used to create prompt cache entries, broken down by cache TTL.

ephemeral_1h_input_tokens: optional number

Tokens used to create 1-hour ephemeral cache entries.

formatint32
ephemeral_5m_input_tokens: optional number

Tokens used to create 5-minute ephemeral cache entries.

formatint32
cache_read_input_tokens: optional number

Total tokens read from prompt cache.

formatint32
input_tokens: optional number

Total input tokens consumed across all turns.

formatint32
list_cost: optional object{ amount, currency }

Cumulative list cost of this thread across all turns, priced at public list rates. Absent until cost tracking is available for the thread. Each figure is rounded to the nearest cent independently and the session's aggregate usage.list_cost additionally includes session runtime, so per-thread costs do not sum exactly to the session figure; the session figure is authoritative and is what a budget is enforced against.

amount: string

Amount in minor units of the currency, as an integer decimal string with no leading zeros: "2500" is $25.00 and "50" is fifty cents. A string rather than a number so no float rounding is ever applied.

currency: "USD"

Uppercase ISO-4217 currency code. USD is the only currency currently supported; the accepted set is closed and grows only when a new currency is priced.

output_tokens: optional number

Total output tokens generated across all turns.

formatint32
server_tool_use: optional object{ web_fetch_requests, web_search_requests }

Cumulative server-executed tool usage across all turns of this thread. Absent until server-tool tracking is available for the thread.

web_fetch_requests: optional number

Number of server-executed web fetch requests.

formatint32
web_search_requests: optional number

Number of server-executed web search requests.

formatint32
workflow_run_id: string

Identifier of the workflow run that created the thread, or null for any other thread.

next_page: optional string

Opaque cursor for the next page. Null when no more results.

List Session Threads
ant beta:sessions:threads list \
  --api-key my-anthropic-api-key \
  --session-id sesn_011CZkZAtmR3yMPDzynEDxu7
Returns Examples
Response 200
{
  "data": [
    {
      "id": "sthr_011CZkZVWa6oJjw1rgXZpnBt",
      "agent": {
        "id": "agent_011CZkYqphY8vELVzwCUpqiQ",
        "description": "A focused research subagent.",
        "mcp_servers": [
          {
            "name": "example-mcp",
            "type": "url",
            "url": "https://example-server.modelcontextprotocol.io/sse"
          }
        ],
        "model": {
          "id": "claude-opus-5-5",
          "effort": {
            "type": "low"
          },
          "inference_geo": "inference_geo",
          "speed": "standard"
        },
        "name": "Researcher",
        "skills": [
          {
            "skill_id": "xlsx",
            "type": "anthropic",
            "version": "1"
          }
        ],
        "system": "You are a research subagent that gathers and summarises sources for the coordinating agent.",
        "tools": [
          {
            "configs": [
              {
                "enabled": true,
                "name": "bash",
                "permission_policy": {
                  "type": "always_allow"
                },
                "type": "bash"
              }
            ],
            "default_config": {
              "enabled": true,
              "permission_policy": {
                "type": "always_ask"
              }
            },
            "type": "agent_toolset_20260401"
          }
        ],
        "type": "agent",
        "version": 1
      },
      "archived_at": null,
      "created_at": "2026-03-15T10:00:00Z",
      "parent_thread_id": null,
      "session_id": "sesn_011CZkZAtmR3yMPDzynEDxu7",
      "stats": {
        "active_seconds": 0,
        "duration_seconds": 0,
        "startup_seconds": 0
      },
      "status": "idle",
      "type": "session_thread",
      "updated_at": "2026-03-15T10:00:00Z",
      "usage": {
        "active_seconds": 0,
        "cache_creation": {
          "ephemeral_1h_input_tokens": 0,
          "ephemeral_5m_input_tokens": 0
        },
        "cache_read_input_tokens": 0,
        "input_tokens": 0,
        "list_cost": {
          "amount": "2500",
          "currency": "USD"
        },
        "output_tokens": 0,
        "server_tool_use": {
          "web_fetch_requests": 0,
          "web_search_requests": 3
        }
      },
      "workflow_run_id": null
    }
  ],
  "next_page": "page_MjAyNS0wNS0xNFQwMDowMDowMFo="
}