CHATBOTS

Weekly Ownership Coverage Audit to Slack

Each week, cross-checks the service catalog against the live service inventory and posts a Slack report of unowned services, missing runbooks, and SLA gaps with direct fix links.

CategoryChatbots
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule fires
  • ActionPull the live service inventory from GitHubGitHubGitHub
  • ActionPull current ownership rows from the Postgres catalogPostgreSQLPostgres
  • LogicDiff inventory vs catalog to find unowned, no-runbook, and SLA gaps
  • ActionWrite this week's coverage snapshot for trend trackingPostgreSQLPostgres
  • OutputPost the grouped coverage report with fix links to SlackSlack

What it does

Gives platform leads a weekly scorecard of ownership hygiene. It compares the catalog against the actual set of deployed services, then posts a Slack report highlighting services with no owner, no runbook link, or no SLA tier set, plus how coverage changed week over week.

When to use it

When you want a recurring, visible accountability signal rather than discovering gaps mid-incident. Good for platform or SRE teams driving an ownership-completeness goal.

How it works

  1. 1A weekly schedule fires.
  2. 2It pulls the live service inventory from GitHub (repos or a manifest of deployed services).
  3. 3It pulls the current catalog rows from Postgres.
  4. 4A logic step diffs the two to find unowned services, missing runbooks, and unset SLA tiers, and computes the delta versus last week's snapshot.
  5. 5It writes this week's coverage snapshot back to Postgres for trend tracking.
  6. 6It posts a formatted Slack report grouping each gap type with links to fix each entry.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitHubRepos, issues, pull requests, actions.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  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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