queue-workflowlisted

# Queue Workflow Use this skill when a task needs more than one serious pass, or when the user explicitly asks for queue workflow. ## Problem AI can fail in two opposite ways: - stop early, act lazy, or treat a green first pass as done - keep "improving" by adding duplicate sections, files, functions, fallbacks, names, or explanations Queue workflow protects against both. It also catches prompt echoing, history leaking, topic drift away from exact `continue`, shallow queued micro-tasks, and review overload for the human. The goal is not to split work into tiny tasks. Each pass, including the current pass and every later queue-runner invocation, must inspect context, do the work, validate, simplify, and report clearly. ## When To Use Use queue-first when: - the user explicitly asks for queue workflow, even for small work - the task is medium or large - code, docs, skill, runbook, or architecture changes may sprawl - regressions, missing tests/docs, naming drift, or duplicate structure are plausible - the user needs a final version, not draft-history explanation inside the artifact Skip it only when the user did not ask for queue workflow and the task is clearly tiny, low-risk, and fully verifiable in one short pass. Read [references/content-architecture.md](references/content-architecture.md) as the structural foundation for both the current pass and queued passes. ## Core Workflow Principles: - Durable queues are an external clisbot queue-runner flow; the curren