Make Operations Idempotent

SkillAI & models

Apply when designing commands, lifecycle steps, or processing loops that run amid crashes, restarts, and retries. Converge to the same end state regardless of partial prior runs.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Make Operations Idempotent skill

What this skill tells your AI

The instructions your AI receives, as published by michael-denyer/pstack-claude in plugins/pstack/skills/principle-make-operations-idempotent/SKILL.md and read by ahel’s review.

Design operations so they converge to the correct state regardless of how many times they run or where they start from. Every state-mutating operation should answer: "What happens if this runs twice? What happens if the previous run crashed halfway?"

Why: Commands, lifecycle operations, and processing loops run where crashes, restarts, and retries are normal. If partial state changes the next run's outcome, every restart becomes a debugging session.

The pattern:

  • Convergent startup: scan for existing state, clean stale artifacts, adopt live sessions
  • Content-based cleanup: compare by content equivalence, not creation order
  • Self-healing locks: use PID-based stale lock detection
  • Idempotent scheduling: failed work respawns cleanly, fresh input regenerated after each cycle

The test:

  1. What happens if this runs twice in a row?
  2. What happens if the previous run crashed at every possible point?
  3. Does re-execution converge to the same end state?

If any answer is "it depends on what state was left behind," the operation needs a reconciliation step.

Signals

GitHub stars
341
Forks
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Last commit
Sep 2026
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Catalog kind
skill
Gateway key
principle-make-operations-idempotent-michael-denyer
Source
github.com/michael-denyer/pstack-claude