Use when refactoring production code and you want to ensure test files are not modified. Activate with /freeze-tests to block all edits to test files for safe refactoring.
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실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
When activated, blocks all modifications to test files. Use during refactoring to ensure behavior (as captured by tests) is preserved.
Blocks Write and Edit operations on any file matching test patterns:
**/*.test.{ts,js,tsx,jsx}**/*.spec.{ts,js,tsx,jsx}**/__tests__/****/tests/**/freeze-tests
Deactivate with /freeze-tests off.
{
"hooks": {
"PreToolUse": [
{
"matcher": "Write|Edit",
"hook": ".claude/skills/freeze-tests/scripts/block-test-edits.sh",
"condition": "file matches **/*.test.* OR **/*.spec.* OR **/__tests__/** OR **/tests/**"
}
]
}
}
#!/bin/bash
# block-test-edits.sh
FILE="$1"
if echo "$FILE" | grep -qP '\.(test|spec)\.(ts|js|tsx|jsx)$|__tests__|/tests/'; then
echo "BLOCKED: Test files are frozen during refactoring."
echo "If tests need updating, deactivate with: /freeze-tests off"
exit 1
fi
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Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
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WCAG 2.2 compliance testing, screen reader validation, and inclusive design verification. Use when ensuring legal compliance (ADA, Section 508), testing for disabilities, or building accessible applications for 1 billion disabled users globally.
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
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Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
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