How to pause your agent for human input

Some tasks reach a decision point the agent cannot resolve on its own — a target environment, an approval threshold, a destructive step that needs sign-off. murmur-tool-request-input gives the model a ready-made tool to pause at that point, surface a question to the operator, and resume exactly where it left off once the operator replies.

The relevant manifest options are:

Option	Controls
artifacts[].runtime	Whether a WASM artifact is a model-visible tool, inference driver, or hook
lifecycle.input_timeout_secs	Maximum seconds to wait before failing the task if no reply arrives

---

Step 1 — write the manifest

Create a murmur.yaml file. Add murmur-tool-request-input to artifacts with runtime: tool, and write a system_prompt that tells the model when to pause:

AnthropicOpenAIDeepSeek

name: my-agent
version: "0.1.0"

network:
  internal_port: 52222

artifacts:
  - name: murmur-driver-anthropic
    version: "1.0.0"
    runtime: driver
  - name: murmur-tool-request-input
    version: "1.0.0"
    runtime: tool

capabilities:
  network:
    allow:
      - https://api.anthropic.com

inference:
  transport: http
  endpoint: https://api.anthropic.com
  model: claude-sonnet-5
  api_key: ${ANTHROPIC_API_KEY}
  driver:
    artifact: murmur-driver-anthropic
  system_prompt: |
    You are a deployment agent. When you reach a decision you cannot make on your own —
    such as which environment to target or whether to proceed with a destructive step —
    call murmur-tool-request-input with a clear, specific question for the operator.

name: my-agent
version: "0.1.0"

network:
  internal_port: 52222

artifacts:
  - name: murmur-driver-openai
    version: "1.0.0"
    runtime: driver
  - name: murmur-tool-request-input
    version: "1.0.0"
    runtime: tool

capabilities:
  network:
    allow:
      - https://api.openai.com

inference:
  transport: http
  endpoint: https://api.openai.com
  model: o3-mini-high
  api_key: ${OPENAI_API_KEY}
  driver:
    artifact: murmur-driver-openai
  system_prompt: |
    You are a deployment agent. When you reach a decision you cannot make on your own —
    such as which environment to target or whether to proceed with a destructive step —
    call murmur-tool-request-input with a clear, specific question for the operator.

name: my-agent
version: "0.1.0"

network:
  internal_port: 52222

artifacts:
  - name: murmur-driver-deepseek
    version: "1.0.0"
    runtime: driver
  - name: murmur-tool-request-input
    version: "1.0.0"
    runtime: tool

capabilities:
  network:
    allow:
      - https://api.deepseek.com

inference:
  transport: http
  endpoint: https://api.deepseek.com
  model: deepseek-r1
  api_key: ${DEEPSEEK_API_KEY}
  driver:
    artifact: murmur-driver-deepseek
  system_prompt: |
    You are a deployment agent. When you reach a decision you cannot make on your own —
    such as which environment to target or whether to proceed with a destructive step —
    call murmur-tool-request-input with a clear, specific question for the operator.

network.internal_port pins the worker capsule to a fixed port on every run. Without it the runtime picks an OS-assigned port at startup, which changes between runs and would invalidate the orchestrator capsule's allow list entry.

runtime: tool registers the WASM component with the capsule runtime. The model sees it as a callable tool named murmur-tool-request-input with one parameter:

Parameter	Type	Required	Description
prompt	string	yes	The question to present to the operator

The system prompt controls when the model pauses. A vague instruction ("ask when unsure") produces over-cautious behavior; a concrete rule ("call the tool before any destructive step") produces predictable escalation.

---

Step 2 — install dependencies

With murmur.yaml in place, fetch all declared artifacts:

mur install

Different ways to install artifacts

mur install needs to know where to fetch artifacts from. You have two options:

Option A — configure a registry source in ~/.murmur/config.yaml:

registry:
  default: official
  sources:
    - name: official
      type: github
      repo: <owner>/<repo>
      token: "${GITHUB_TOKEN}"

Then install by artifact name and version:

mur install <artifact-name@version>

Option B — pass a full GitHub reference and skip configuration entirely:

mur install github:<username>/<repo>@<tag>

See Installing artifacts to learn more.

murmur-tool-request-input is a WASM artifact — no platform tag is required. mur install resolves the correct variant for every artifact in the manifest automatically.

---

Step 3 — run the capsule and send a task

Start the capsule:

mur run
murmur: url localhost:52222
session: ses_019ed2af53da75c2aefee84ee10c34af

Note the URL. Set a shell variable for convenience, replacing 52222 with the port you see:

PORT=52222

Send a task that will require a human decision:

curl -s -X POST http://localhost:$PORT \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "message/send",
    "params": {
      "message": {
        "messageId": "msg-001",
        "role": "user",
        "parts": [{"text": "Deploy the latest build. Confirm the target environment before proceeding."}]
      }
    }
  }'

Response:

{
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "id": "tsk_01jw...",
    "contextId": "ctx_01jw...",
    "status": { "state": "submitted" }
  }
}

Save the task id — you will need it to detect the pause.

---

Step 4 — detect when the agent is waiting

Poll tasks/get with the task ID until the state changes to input-required:

curl -s -X POST http://localhost:$PORT \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":2,"method":"tasks/get","params":{"id":"<your_task_id>"}}'

While the agent is waiting, the response includes the question it formed:

{
  "jsonrpc": "2.0",
  "id": 2,
  "result": {
    "id": "tsk_01jw...",
    "contextId": "ctx_01jw...",
    "status": { "state": "input-required" },
    "artifacts": [
      {
        "name": "prompt",
        "parts": [{ "text": "Which environment should I deploy to? (staging, production)" }]
      }
    ]
  }
}

The agent's question is at result.artifacts[0].parts[0].text. Read it and decide your answer.

---

Step 5 — send your answer

Send a message to the same capsule URL:

curl -s -X POST http://localhost:$PORT \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": 3,
    "method": "message/send",
    "params": {
      "message": {
        "messageId": "reply-001",
        "role": "user",
        "parts": [{"text": "staging"}]
      }
    }
  }'

The answer is delivered directly to the suspended tool call. The agent receives "staging" as the tool result and the loop resumes immediately:

{
  "jsonrpc": "2.0",
  "id": 3,
  "result": {
    "id": "tsk_01jw...",
    "contextId": "ctx_01jw...",
    "status": { "state": "working" }
  }
}

Poll tasks/get again until state reaches completed or failed.

---

Optional — set an input timeout

To fail the task automatically if no reply arrives within a deadline, add lifecycle.input_timeout_secs to the manifest:

lifecycle:
  task_acceptance: single
  input_timeout_secs: 300

When the deadline passes, the task transitions to state: "failed" with message "input-timeout". Omit the field to wait indefinitely.

---

Summary

Feature / setting	How it works
murmur-tool-request-input	WASM tool artifact; runtime: tool; platform-independent
prompt parameter	The question the model asks the operator; string, required
Task state while waiting	"input-required"
Where to read the question	result.artifacts[0].parts[0].text from tasks/get
How to resume the agent	Send a message to the same capsule URL
State after reply	"working" immediately; poll until "completed"
lifecycle.input_timeout_secs	Integer seconds to wait for a reply; absent = wait indefinitely