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.
中文简介正在准备中。当前显示原文说明。
Use when reviewing which QE skills are being used, finding undertriggering skills, or analyzing skill effectiveness. Shows usage patterns and recommendations.
中文简介正在准备中。当前显示原文说明。
实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
View QE skill usage patterns to identify popular skills, undertriggering skills, and optimization opportunities.
/skill-stats
Skill invocations are logged to ${CLAUDE_PLUGIN_DATA}/skill-usage.log:
2026-03-18T10:30:00Z|security-testing|explicit|/security-testing
2026-03-18T10:45:00Z|qe-test-generation|auto|model-selected
2026-03-18T11:00:00Z|mutation-testing|explicit|/mutation-testing
{
"hooks": {
"PreToolUse": [
{
"matcher": "Skill",
"hook": ".claude/skills/skill-stats/scripts/log-usage.sh"
}
]
}
}
#!/bin/bash
# analyze-usage.sh
LOG="${CLAUDE_PLUGIN_DATA:-$HOME/.claude/plugin-data}/skill-usage.log"
if [ ! -f "$LOG" ]; then
echo "No usage data yet. Skills will be logged as they are used."
exit 0
fi
echo "=== Skill Usage Report ==="
echo ""
echo "Top 10 Most Used:"
cut -d'|' -f2 "$LOG" | sort | uniq -c | sort -rn | head -10
echo ""
echo "Trigger Method Breakdown:"
cut -d'|' -f3 "$LOG" | sort | uniq -c | sort -rn
echo ""
echo "Skills Used in Last 7 Days:"
WEEK_AGO=$(date -d '7 days ago' +%Y-%m-%dT%H:%M:%S 2>/dev/null || date -v-7d +%Y-%m-%dT%H:%M:%S)
awk -F'|' -v since="$WEEK_AGO" '$1 >= since' "$LOG" | cut -d'|' -f2 | sort | uniq -c | sort -rn
tail -n 1000 $LOG > $LOG.tmp && mv $LOG.tmp $LOG还没有评价。欢迎分享你的使用感受。
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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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。