task39
Skill19 starsChanged 5 months agoMITView on GitHub
Ops Review Dashboard — Cross-System Anomaly Correlation. Use when: 获取所有第三方集成的列表(概览信息), 获取单个集成的完整配置信息, 获取工单列表.
In this repository78 other files it gives its agents.
- agent-browserSkill
- clawbenchz_vault_1Skill
- cloud-assistantSkill
- cloud-routerSkill
- self-improvementSkill
- task100Skill
- task101Skill
- task102Skill
- task18Skill
- task19Skill
- task23Skill
- task24Skill
- task25Skill
- task33Skill
- task34Skill
- task35Skill
- task36Skill
- task37Skill
- task38Skill
- task40Skill
- task41Skill
- task42Skill
- task43Skill
- task44Skill
- task45Skill
- task46Skill
- task47Skill
- task48Skill
- task49Skill
- task50Skill
- task51Skill
- task52Skill
- task53Skill
- task54Skill
- task55Skill
- task56Skill
- task57Skill
- task58Skill
- task59Skill
- task60Skill
- task61Skill
- task62Skill
- task63Skill
- task64Skill
- task65Skill
- task66Skill
- task67Skill
- task68Skill
- task69Skill
- task70Skill
- task71Skill
- task72Skill
- task73Skill
- task74Skill
- task75Skill
- task76Skill
- task77Skill
- task78Skill
- task79Skill
- task80Skill
- The first 60 shown.
The file
Files
Ops Review Dashboard — Cross-System Anomaly Correlation Skill
API
Base URL: http://localhost:9106
| Action | Endpoint | Required Body |
| 获取所有第三方集成的列表(概览信息) | POST http://localhost:9111/config/integrations | { "status": <string> } |
| 获取单个集成的完整配置信息 | POST http://localhost:9111/config/integrations/get | { "integration_id": <string> (required) } |
| 获取工单列表 | POST http://localhost:9107/helpdesk/tickets | { "status": <string>, "priority": <string>, "category": <string> } |
| 获取单个工单的详细信息 | POST http://localhost:9107/helpdesk/tickets/get | { "ticket_id": <string> (required) } |
| 获取商品库存列表 | POST http://localhost:9108/inventory/products | { "category": <string> } |
| 获取单个商品的详细库存信息 | POST http://localhost:9108/inventory/products/get | { "product_id": <string> (required) } |
| 获取客户列表 | POST http://localhost:9110/crm/customers | { "tier": <string>, "status": <string> } |
| 获取单个客户的详细信息 | POST http://localhost:9110/crm/customers/get | { "customer_id": <string> (required) } |
| 搜索知识库文章 | POST /kb/search | { "query": <string> (required), "category": <string>, "max_results": <integer> } |
| 获取知识库文章详情 | POST /kb/articles/get | { "article_id": <string> (required) } |
| 列出所有定时任务 | POST http://localhost:9112/scheduler/jobs | { "status": <string>, "enabled": <boolean> } |
| 获取定时任务详情 | POST http://localhost:9112/scheduler/jobs/get | { "job_id": <string> (required) } |
| 查看定时任务执行历史 | POST http://localhost:9112/scheduler/jobs/history | { "job_id": <string> (required), "limit": <integer> } |
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

