Maintenance AI Agent Loops

Maintenance loops for dependencies, stale content, and recurring quality checks. Every page is server-rendered, source-aware, and includes a copy-ready Markdown protocol.

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All Maintenance loops

Maintenancemanual trigger Hardened

Dependency Upgrade Safety Loop

Upgrade dependencies in small batches, inspect install scripts, and verify build/test behavior after each batch.

Claude CodeCodexGemini CLIOpenCode

dependenciesupgradesupply-chain

Kickoff preview

Upgrade dependencies in small safe batches, review install-time scripts, run build/tests after each batch, and document remaining breaking changes.
Goal: Upgrade dependencies without breaking the app or ignoring supply-chain risk.
Check command: pnpm build
Exit condition: Selected dependency batch is upgraded and validation passes.
Max iterations: 5
Guardrails:
- Do not weaken, skip, delete, or rewrite the validation command to force success.
- Do not claim completion until the stated exit condition is actually satisfied.
- If blocked, report the blocker, evidence, and next safest action instead of gaming the metric.
- Do not blindly install packages without reviewing install/postinstall/prepare scripts.

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Why this category matters

Maintenance loops are useful because AI agents need explicit feedback gates and exit criteria. A plain prompt may produce a first draft; a loop tells the agent how to verify progress, handle failures, and stop with evidence.