Burn through the backlog from hell with /triage

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• Introduces the /triage Claude Code skill for managing GitHub issue backlogs at scale — argues that messy human-written issues need to be translated into structured, machine-actionable tasks before AI agents can work on them effectively.
• Uses state machines and labels as the mechanism for categorising issues: the triage step isn’t just sorting, it’s a translation layer from human intent to agent-legible state.
• Core insight: the bottleneck in AI-driven development is often not the agent’s capability but the quality of its input — badly-specified issues are a tax on every subsequent step.