AI AGENTS

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.

CategoryAI Agents
Enginepaperclip
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule fires
  • ActionQuery Sentry for issues resolved in last 7 daysSentrySentry
  • ActionCheck docs repo coverage for each issueGitHubGitHub
  • LogicScore and rank gaps by severity and recurrence
  • ActionAgent writes digest entries with suggested PR scope
  • OutputPost prioritized doc-gap digest to SlackSlack

What it does

Rather than reacting to every single resolution, this runs on a weekly cadence. It scans all Sentry issues resolved in the past week, evaluates each against existing runbook coverage, and produces a ranked digest of the biggest documentation gaps — frequent pagers with no runbook, recurring errors with stale fixes — and posts it to Slack so the team can triage doc debt in standup.

When to use it

Good for teams that want a steady, low-noise rhythm of paying down documentation debt instead of a PR per incident. Pairs well with a weekly reliability review.

How it works

  1. 1A weekly schedule kicks off the run.
  2. 2The agent queries Sentry for all issues resolved in the trailing 7 days, with frequency and impact metadata.
  3. 3For each, it checks the GitHub docs repo for existing coverage and scores the gap by severity and recurrence.
  4. 4It ranks the gaps and writes a short rationale for the top items.
  5. 5It posts a prioritized digest to Slack, each entry linking to the Sentry issue with a suggested doc-PR scope.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SentryErrors, performance, releases.
  2. 2
    Connect GitHubRepos, issues, pull requests, actions.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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