AI AGENTS
On-call agent: Slack slash-command runbook on-demand executor
An engineer invokes a Slack command naming a runbook; the agent previews the exact shell steps inline and executes them one at a time only as each is confirmed.
How it runs
The automated pipeline, trigger to output.
- TriggerSlack command names runbook and targetSlack
- ActionRender step with exact shell commandSlack
- LogicWait for per-step confirm or abort
- ActionExecute confirmed command, capture outputShell
- OutputPost full command transcript to SlackSlack
What it does
Lets on-call run a known runbook from Slack without opening a terminal. The agent shows the exact command for each step, waits for a confirm, runs it, shows output, then advances — a guided, auditable walk-through.
When to use it
Use it for well-understood recurring procedures (restart a stuck consumer, clear a poison message) where you want speed plus a confirm gate on every command.
How it works
- 1An engineer triggers a Slack command naming the runbook and target.
- 2The agent loads the runbook and renders step one with its exact shell command and purpose.
- 3The engineer confirms; the shell action runs that single command and posts stdout, stderr, and exit code.
- 4The agent advances to the next step and repeats the confirm-run-show loop.
- 5At the end it posts a full transcript of commands and outputs as the incident record.
- 6The engineer can abort at any step, leaving the system in a known partial state.
Set it up
What you configure once, before turning it on.
- 1Connect SlackChannels, DMs, threads, mentions.
- 2Connect ShellRun sandboxed commands inside the workspace.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More AI Agents workflows
Custom Metrics Cardinality Spike Pager
A webhook from a Datadog monitor fires when custom-metric cardinality jumps; an agent pinpoints the offending metric and tag, estimates the added cost.
Sentry-to-Confluence Runbook Updater
When a Sentry issue is resolved, the agent finds the matching Confluence runbook page and proposes an inline update with the verified fix.
Stale Doc-PR Chaser for Runbook Gaps
On a daily schedule the agent finds runbook doc PRs that were opened from resolved incidents but never reviewed, summarizes what each one fixes.
Resolved Incident to Public Troubleshooting Doc
For customer-facing errors resolved in Sentry, the agent drafts a sanitized troubleshooting entry and opens a PR to your ReadMe documentation.
On-Call Runbook Gap Closer: Resolved Sentry Issues to Doc PRs
An agent reads each newly resolved Sentry issue, compares the actual fix against your existing runbook, and opens a GitHub PR adding the missing remediation steps.
Weekly On-Call Doc-Gap Digest
Each week the agent reviews every Sentry issue resolved in the last 7 days, ranks the ones whose runbook coverage is missing or thin.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
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