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refactor(plugin): rename reference skills, make non-user-invocable
Remove ai-dlc- prefix from reference skill directories and names (completion-criteria, blockers, fundamentals, backpressure) and set user-invocable: false so they are only triggered contextually. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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README.md

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This plugin provides skills for understanding AI-DLC:
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- `ai-dlc-fundamentals` - Core principles and philosophy
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- `ai-dlc-completion-criteria` - Writing effective criteria
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- `ai-dlc-mode-selection` - HITL vs OHOTL vs AHOTL
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- `ai-dlc-backpressure` - Using quality gates effectively
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- `ai-dlc-blockers` - Documenting blockers properly
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- `fundamentals` - Core principles and philosophy
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- `completion-criteria` - Writing effective criteria
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- `backpressure` - Using quality gates effectively
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- `blockers` - Documenting blockers properly
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## Error Recovery
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plugin/skills/ai-dlc-backpressure/SKILL.md renamed to plugin/skills/backpressure/SKILL.md

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---
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name: ai-dlc-backpressure
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name: backpressure
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description: Use when implementing or understanding backpressure in AI-DLC workflows. Covers quality gates, Stop hooks, and how automated enforcement guides AI behavior toward quality.
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user-invocable: false
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allowed-tools:
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- Read
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- Bash
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---
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name: ai-dlc-blockers
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name: blockers
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description: Use when documenting blockers in AI-DLC workflows. Covers proper blocker documentation, categorization, and how blockers enable productive iteration when stuck.
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user-invocable: false
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allowed-tools:
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- Read
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- Grep

plugin/skills/ai-dlc-completion-criteria/SKILL.md renamed to plugin/skills/completion-criteria/SKILL.md

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name: ai-dlc-completion-criteria
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name: completion-criteria
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description: Use when defining completion criteria for AI-DLC tasks. Covers writing verifiable, specific, and measurable criteria that enable autonomous operation and clear exit conditions.
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user-invocable: false
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allowed-tools:
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- Read
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- Grep

plugin/skills/ai-dlc-fundamentals/SKILL.md renamed to plugin/skills/fundamentals/SKILL.md

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name: ai-dlc-fundamentals
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name: fundamentals
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description: Use when understanding AI-DLC methodology fundamentals. Covers core principles, iteration patterns, hat-based workflows, and the philosophy of human-AI collaboration in software development.
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user-invocable: false
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allowed-tools:
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- Read
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The AI can't complete work until tests pass. It learns to write tests and fix failures, not because a process document says to, but because the system won't let it proceed otherwise.
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*For detailed backpressure guidance, see the `ai-dlc-backpressure` skill.*
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*For detailed backpressure guidance, see the `backpressure` skill.*
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### 2. Completion Criteria Enable Autonomy
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- Human review becomes targeted ("Did you meet criteria X?")
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- Iteration loops have clear exit conditions
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*For detailed criteria guidance, see the `ai-dlc-completion-criteria` skill.*
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*For detailed criteria guidance, see the `completion-criteria` skill.*
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### 3. Files Are Memory
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