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Open issue. Don’t open the dashboard. Come back in five minutes to a ready PR labeled human:review. The pipeline on this repo, dryvist/docs, uses six thin caller files in .github/workflows/ that delegate to reusable workflows in JacobPEvans/.github-ai. Each caller is 10–30 lines; the AI work all lives in the upstream reusable workflow.

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What runs, in order

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How the six callers connect

The hub is the consumer repo; each caller is a one-shot wrapper around an upstream reusable workflow. They run independently when their trigger fires.

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What each caller actually contains

A caller is the minimum YAML to declare a trigger, set permissions, and call the upstream:
Two patterns are slightly larger:
  • post-merge-docs-review.yml uses the Post-Merge Dispatch Pattern. It is a two-job file because push events aren’t supported by claude-code-action@v1, so the caller re-dispatches as workflow_dispatch.

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Secrets the pipeline needs

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Rate and safety guards

The reusable workflows enforce conservative defaults so a runaway loop can’t burn cloud spend:
  • issue-resolver.yml: max_attempts: 1 per issue, daily_limit: 5 per repo, and it skips any issue labeled excluded_labels: "type:security,type:feature,type:breaking,size:l,size:xl"
  • All workflows: fork PRs blocked by if: guards, branch protection enforces the final merge gate

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The pieces this doesn’t include

The cloud pipeline opens a ready PR labeled human:review and provides AI review. It does NOT:
  • Mark the PR ready for merge: that’s a human decision
  • Click the merge button: never automated
  • Override branch protection or required reviewers
  • Touch repos outside the current org boundary
For the local iteration loop on a PR you’re editing yourself, see /ship and /finalize-pr.

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Where to go next

ai-workflows

Reusable workflows, pinned catalog prompts, event-triggered and scheduled.

claude-code-routines

The cron half: six routines that scan the org and pick up loose ends.

ai-workflows getting started

Caller templates and the live workflow catalog.

Authentication

AI_TOKEN, provider routing, and model variables.