AI AGENTS
On-call agent: Honeycomb auto-remediate low-risk with Linear incident record
For pre-approved low-risk Honeycomb alerts, an agent auto-runs the runbook shell fix, verifies recovery, and files a Linear incident; anything else escalates to Slack for approval.
How it runs
The automated pipeline, trigger to output.
- TriggerHoneycomb trigger fires with alert typeHoneycomb
- LogicCheck alert type against auto-remediate allowlist
- ActionRun runbook shell fix automaticallyShell
- ActionRe-query Honeycomb to verify recoveryHoneycomb
- ActionFile Linear incident with full recordLinear
- OutputEscalate to Slack if not allowlisted or unverifiedSlack
What it does
Closes the loop fully on the safe, boring alerts. For alert types you have explicitly allowlisted as low-risk, the agent runs the runbook shell fix automatically, confirms the metric recovered, and logs a Linear incident. Everything outside the allowlist falls back to human approval.
When to use it
Use it once you trust a specific class of remediation (clearing a known transient queue backup) enough to automate it, while keeping a hard gate on everything else.
How it works
- 1A Honeycomb trigger fires with the alert type and breaching query.
- 2The agent checks the alert type against the auto-remediate allowlist.
- 3If allowlisted, it runs the runbook's shell fix and then re-queries Honeycomb to verify the metric recovered.
- 4It files a Linear incident capturing the alert, command run, and verification result.
- 5If not allowlisted or if verification fails, it escalates to Slack with a gated proposal for a human.
Set it up
What you configure once, before turning it on.
- 1Connect HoneycombDistributed traces and queries.
- 2Connect ShellRun sandboxed commands inside the workspace.
- 3Connect LinearIssues, projects, cycles, triage.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More AI Agents workflows
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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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