AI AGENTS
Slack Command Runbook Executor for Cloudflare WAF
An on-call engineer types a remediation request in Slack; the agent maps it to a documented runbook, executes the Cloudflare WAF change after confirmation.
How it runs
The automated pipeline, trigger to output.
- TriggerSlack remediation command receivedSlack
- ActionMatch request to runbook and propose exact WAF changeCustom MCP server
- LogicWait for in-thread confirmation or cancel
- ActionApply confirmed Cloudflare WAF rule changeCloudflare
- OutputReply in-thread with diff, rule ID, and rollback commandSlack
What it does
Lets on-call engineers run documented WAF remediations from Slack in plain language. The agent interprets the request, finds the matching runbook, asks for confirmation on the exact change, applies it to Cloudflare, and reports back in the same thread.
When to use it
Use it when you want a human-in-the-loop remediation path: the engineer decides what to do, but the agent handles the runbook lookup and the precise Cloudflare API call so nobody fat-fingers a rule under pressure. Great for ad-hoc incidents that do not start from an automated alert.
How it works
- 1An engineer posts a remediation request via a Slack slash command or mention.
- 2The agent matches the request to a runbook pulled from the MCP server and proposes the exact WAF change.
- 3A logic step waits for the engineer to confirm or cancel in-thread.
- 4On confirmation, the agent applies the Cloudflare WAF rule change.
- 5It replies in-thread with the diff, the rule ID, and a rollback command.
Set it up
What you configure once, before turning it on.
- 1Connect SlackChannels, DMs, threads, mentions.
- 2Connect CloudflareWorkers, Pages, R2, KV — the edge stack.
- 3Connect Custom MCP serverConnect any MCP-compatible tool you own.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, 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.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.
