wenerme/ai
Use when querying or analyzing Tencent Cloud CLS (Cloud Log Service) logs: writing CQL search queries, performing SQL analysis on log data, using CLS MCP tools (search, cluster_logs, log_context, histogram), or troubleshooting CLS query issues.
npx skills add wenerme/ai --skill tencent-cls
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npx skills add wenerme/ai
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SUMMARY.md
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腾讯云日志服务 (CLS) 查询与分析指南。
level:"ERROR" not level:ERRORAnalysis: falsecast(TIMESTAMP as timestamp) for time operations in SQL analysiskey:"value" # 键值搜索（字符串必须加引号）
key:123 # 数值搜索
value # 全文搜索
level:"ERROR" AND pid:1 # 逻辑与
status:>400 # 范围查询
host:*test* # 通配符
field:* # 字段存在
NOT key:"value" # 排除AND 优先级高于 OR，建议用括号明确：
(A OR B) AND C
| 工具 | 用途 | 关键参数 |
|---|---|---|
search |
搜索日志 | topic, query, from, limit, format |
cluster_logs |
聚类相似日志 | topic, query, field, simTh |
log_context |
获取日志上下文 | topic, time, pkgId, pkgLogId |
histogram |
时间分布统计 | topic, query, from, buckets |
# 搜索日志
mcp-cli call <cls-server>/search '{"topic":"my-topic","query":"level:\"ERROR\"","from":"-6h","limit":50}'
# 聚类分析
mcp-cli call <cls-server>/cluster_logs '{"topic":"my-topic","query":"level:\"ERROR\"","from":"-3d"}'
# 日志上下文
mcp-cli call <cls-server>/log_context '{"topic":"my-topic","time":"...","pkgId":"...","pkgLogId":"..."}'
# 时间分布
mcp-cli call <cls-server>/histogram '{"topic":"my-topic","from":"-24h","buckets":24}'用于展示业务流量随时间的变化。
* | SELECT histogram(cast(__TIMESTAMP__ as timestamp), interval 1 minute) as time,
count(*) as pv,
count(distinct remote_addr) as uv
GROUP BY time ORDER BY time DESC LIMIT 10000分析不同协议（如 HTTP, HTTPS）的流量分布。
* | SELECT histogram(cast(__TIMESTAMP__ as timestamp), interval 1 minute) as time,
protocol_type,
count(*) as pv
GROUP BY time, protocol_type ORDER BY time DESC LIMIT 10000计算不同 HTTP 状态码分布及其比例，监控服务质量。
* | SELECT date_trunc('minute', __TIMESTAMP__) as time,
round(sum(case when status = 404 then 1.00 else 0.00 end) / cast(count(*) as double) * 100, 3) as "404比例",
round(sum(case when status >= 500 then 1.00 else 0.00 end) / cast(count(*) as double) * 100, 3) as "5XX比例",
round(sum(case when status >= 400 and status < 500 then 1.00 else 0.00 end) / cast(count(*) as double) * 100, 3) as "4XX比例",
round(sum(case when status >= 400 then 1.00 else 0.00 end) / cast(count(*) as double) * 100, 3) as "总失败率"
GROUP BY time ORDER BY time LIMIT 10000