Return External Tool Execution to Slack
Pause on a Kubernetes diagnostic the Agent cannot execute.
Pause on a Kubernetes diagnostic the Agent cannot execute. Slack displays the tool name and command argument, then collects the operator's external result.
"""
Return External Tool Execution to Slack
=======================================
Pause on a Kubernetes diagnostic the Agent cannot execute. Slack displays the
tool name and command argument, then collects the operator's external result.
Prerequisites: SLACK_TOKEN, SLACK_SIGNING_SECRET, OPENAI_API_KEY
Run: .venvs/demo/bin/python cookbook/05_agent_os/17_slack/hitl_external_execution.py
Try in Slack: Ask "Check api-gateway pods in the production namespace."
Slack scopes: app_mentions:read, assistant:write, chat:write, im:history
"""
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses
from agno.os import AgentOS
from agno.os.interfaces.slack import Slack
from agno.tools import tool
from agno.tools.websearch import WebSearchTools
runbooks = {
"CrashLoopBackOff": "Inspect lastState, then check previous logs and memory limits.",
"ImagePullBackOff": "Verify the image tag and the ServiceAccount imagePullSecrets.",
"Pending": "Inspect scheduling events, requested resources, and node selectors.",
}
@tool(external_execution=True)
def run_kubectl(command: str) -> str:
"""Represent a kubectl command that the operator executes outside AgentOS."""
return command
@tool
def lookup_runbook(symptom: str) -> str:
"""Return internal remediation guidance for a Kubernetes pod symptom."""
return runbooks.get(symptom, f"No internal runbook found for {symptom}.")
# ---------------------------------------------------------------------------
# Create External-execution Slack AgentOS
# ---------------------------------------------------------------------------
db = SqliteDb(
id="slack-hitl-external-db",
db_file="tmp/slack_hitl_external.db",
)
devops_agent = Agent(
id="slack-devops-agent",
name="Slack DevOps Agent",
model=OpenAIResponses(id="gpt-5.5"),
db=db,
tools=[run_kubectl, lookup_runbook, WebSearchTools()],
instructions=[
"For pod-health requests, call run_kubectl with the complete command argument.",
"The Python entrypoint does not run before the pause. Slack displays the "
"tool name and command argument, then collects the operator's external result.",
"Analyze the submitted output and count healthy and unhealthy pods.",
"Prefer lookup_runbook for a recognized symptom; use web search only as fallback.",
],
markdown=True,
)
agent_os = AgentOS(
id="slack-hitl-external-os",
description="AgentOS resuming an externally executed tool through Slack.",
db=db,
agents=[devops_agent],
interfaces=[Slack(agent=devops_agent)],
)
app = agent_os.get_app()
# ---------------------------------------------------------------------------
# Run External-execution Slack AgentOS
# ---------------------------------------------------------------------------
if __name__ == "__main__":
agent_os.serve(app=app)The Kubernetes tool pauses for an operator to provide its result. This Python example does not execute kubectl; the operator runs any real diagnostic in their own environment and submits the output. The web search tool can still make external requests.
Run the Example
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activatePrepare the Slack app
Follow Slack setup to create and install the app, obtain its bot token and signing secret, and configure its current agent experience. Add the bot scopes listed in this example's source docstring and reinstall after changing scopes. Subscribe to app_mention and message.im; configure interactivity for buttons and forms.
Install ngrok and run ngrok http 7777 in another terminal. Keep the tunnel running. After starting this example's server, use the callback paths listed on this page under your public HTTPS URL and complete Slack's verification challenge. Configure each app separately for a multi-app example.
Streaming requires the corresponding Slack app capability. The current Agno adapter initializes suggested prompts on the legacy assistant_thread_started event; the setup guide explains the new-app limitation. Keep only one standalone example on port 7777 at a time.
Install dependencies
uv pip install -U "agno[os,slack]" ddgs openaiExport environment variables
export OPENAI_API_KEY="your_openai_api_key_here"
export SLACK_SIGNING_SECRET="your_slack_signing_secret_here"
export SLACK_TOKEN="your_slack_token_here"Run the example
Save the code above as hitl_external_execution.py, then run:
python hitl_external_execution.pyConnect Slack to the running server
Keep Python and ngrok running. In each app's Slack settings, prepend your public HTTPS origin to these paths:
| App | Event subscriptions | Interactivity |
|---|---|---|
| Slack app | /slack/events | /slack/interactions |
Complete URL verification, then send a DM or invite the app to a channel and @mention it. Ordinary channel replies require an @mention with the default configuration.
Full source: cookbook/05_agent_os/17_slack/hitl_external_execution.py