AI AGENTS
Comment Window Deadline Watch and Escalation
Tracks comment-period deadlines for watched dockets and escalates to PagerDuty and Slack as the closing window approaches if no rebuttal has been filed.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily deadline sweep schedule
- ActionConfirm comment-close date per docketFirecrawl
- LogicCompute days left and check filing status
- LogicSet escalation level by urgency
- ActionSend Slack reminder for near deadlinesSlack
- OutputPage on-call when window closing unfiledPagerDuty
What it does
This agent maintains awareness of every watched docket's comment deadline. Each day it checks how much time remains and whether your team has logged a filed response. As a deadline nears with no response on record, it escalates with increasing urgency, ending in a PagerDuty page if the window is about to close.
When to use it
Use it when missing a comment deadline carries real cost and your team juggles multiple concurrent rulemakings. It guarantees that an open window with no filed response never slips silently past the cutoff.
How it works
- 1A daily scheduled trigger starts the deadline sweep.
- 2Firecrawl scrapes each watched docket to confirm the current comment-close date.
- 3A logic step computes days remaining and checks the filing-status table for a logged response.
- 4A branch sets escalation level: a Slack reminder when days are low, a PagerDuty page when the window is closing and nothing is filed.
- 5The appropriate alert is dispatched to the on-call owner.
Set it up
What you configure once, before turning it on.
- 1Connect FirecrawlCrawl, scrape, structured extract.
- 2Connect SlackChannels, DMs, threads, mentions.
- 3Connect PagerDutyIncidents, on-call, escalations.
- 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.
