Cloud agent automation backlog

Date: 2026-03-28
Status: Proposal — prioritization only; no implementation commitment in this PR.

Prioritized ideas for cloud-agent automations tailored to this monorepo, grounded in existing GitHub Actions and internal plans, so new agents add net value without duplicating CI.

Follow-up work (from planning)

  • Dagster CI vs agent: Decide whether to extend .github/workflows/ci.yml for apps/dagster-pipelines/** or use a dedicated cloud agent that runs pytest and comments.
  • PR hygiene + secret scan: Spec triggers (opened/edited) and checks: PR template sections, Linear ID in title, diff patterns for secrets.
  • dbt impact (phase 1): Scope paths, dbt project location, compile-only vs test + diff.

What you already have (avoid duplicating)

A typical cloud stack (skill audit, test coverage, docs, vuln scan) complements this; the highest-value new agents fill gaps CI does not cover or orchestrate cross-cutting checks with human-readable PR comments.


Tier 1 — Highest impact / efficacy for a cloud agent

AutomationWhy it matters hereEfficacy notes
Dagster/Python PR gate + summaryAGENTS.md states Dagster changes should run pytest pipelines_tests until dedicated Python CI exists; today main CI does not gate apps/dagster-pipelines/**.Agent checks out PR, venv + pip install, runs pytest, posts a short pass/fail summary + failing test names. Very high signal per run.
dbt / analytics PR impact reportCloud agent data environment report calls “dbt PR impact” the highest-leverage data move: modified models, compile/test, risk narrative.Fits long-running, judgment-heavy work agents do well; can start read-only (compile + dbt ls / graph summary) before full diff automation.
PR hygiene bot (description + Linear title)Cursor rules (e.g. .cursor/rules/github-pr-description.mdc, .cursor/rules/linear-github-branch.mdc) require PR body sections and Linear ID in title for integration.Cheap to run on opened/edited; high team leverage, low flake rate. Post a checklist comment or ✅ when satisfied.
Secret-leak / env-in-diff scannerComplements generic “vuln scan”: catch accidental .env, API keys, op:// mishaps in the diff.Rules like .cursor/rules/no-secrets-in-repo.mdc encode intent; automation enforces it on every PR.

Tier 2 — Strong value, slightly narrower or more maintenance

AutomationWhyCaveats
Monorepo path routerPRs can touch apps/platform/, apps/dagster-pipelines/, and apps/paperclip/ with different install/build commands. Some work also hands off to separate repos such as brainforge-work.Agent comments “run these checks locally” or triggers awareness; avoid fighting existing per-app workflows under apps/*/.github/.
Subtree / integration drift nudgeDagster is still a subtree in AGENTS.md, while Work has moved to a separate repo and still has Platform handoff points.On changes under those surfaces, comment with the right sync/playbook docs; efficacy depends on keeping links current.
CI failure explainer (non-auto-fix)When CI fails and Codex auto-fix does not apply (E2E, Slack tests, wrong cwd), agent summarizes logs and suggests next step.Useful when failures are env/credentials vs code; avoid duplicating Codex’s lint/types loop.
Dependency / lockfile consistencyPlatform uses npm ci --legacy-peer-deps in CI; lockfile drift causes churn.Agent flags package.json changed without package-lock.json, or documents required follow-up.

Tier 3 — Nice-to-have

  • Stale PR / review SLA ping (Slack or comment): process, not repo-specific.
  • Post-merge smoke reminder (e.g. Railway health): only if wired to deploy URLs and secrets policy allows.
  • Structured PR security summary comment: overlaps PR Agent + vuln scan; only add if you want an OWASP-style template distinct from existing tools.

Suggested order to implement

  1. Dagster pytest on PRs (or widen ci.yml with a paths job) — closes a real quality hole.
  2. PR hygiene + secret-in-diff — minimal cost, aligns with team rules.
  3. dbt impact report — strategic for data work; phase as compile-only then expand.