AI AGENTS
Postmortem Remediation Audit and Laggard Re-opener
Audits last quarter's incident action items in Linear, verifies which remediations actually shipped, and automatically re-opens the ones that quietly went stale.
How it runs
The automated pipeline, trigger to output.
- TriggerQuarter-start schedule fires
- ActionPull prior-quarter incident action items from LinearLinear
- ActionSearch GitHub for shipping evidence per itemGitHub
- LogicSplit items into shipped vs. unverified
- ActionRe-open unverified items with evidence-gap commentLinear
- OutputPost laggard digest to incidents Slack channelSlack
What it does
Every quarter, incident postmortems generate a pile of remediation action items — and most teams never confirm they were actually completed. This agent pulls last quarter's incident action items from Linear, cross-checks each against shipped evidence (closed PRs, deploy tags, merged config changes via GitHub), and re-opens any item marked done that has no shipping evidence. It posts a digest of the laggards to Slack so owners can't pretend the work landed.
When to use it
Run it at the start of each quarter, or before an incident review meeting, when you need ground truth on whether your reliability backlog is real progress or theater.
How it works
The scheduled trigger fires at quarter start. The agent queries Linear for action items labeled `incident` created in the prior quarter. For each one marked Done, it searches GitHub for a linked PR or deploy referencing the item. A logic step splits items into shipped vs. unverified. Unverified items are re-opened in Linear with a comment citing the missing evidence, and a summary of every re-opened laggard is delivered to the incidents Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect LinearIssues, projects, cycles, triage.
- 2Connect GitHubRepos, issues, pull requests, actions.
- 3Connect SlackChannels, DMs, threads, mentions.
- 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
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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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