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../infrahub-check-creator/SKILL.md../infrahub-transform-creator/SKILL.md../infrahub-check-creator/SKILL.md../infrahub-transform-creator/SKILL.md| Priority | Category | Prefix | Description |
|---|---|---|---|
| CRITICAL | MCP Tools | | Available Infrahub MCP tools, invocation patterns, response structure |
| CRITICAL | Query Patterns | | GraphQL structures for fetching, filtering, and traversing relationships |
| HIGH | Correlation | | Joining, diffing, and reasoning over data from multiple queries |
| HIGH | Reporting Output | | Presenting findings: summaries, tables, per-object detail, remediation hints |
| MEDIUM | Approach Selection | | When to use MCP analysis vs InfrahubCheck vs Transform |
| 优先级 | 分类 | 前缀 | 描述 |
|---|---|---|---|
| CRITICAL | MCP工具 | | 可用的Infrahub MCP工具、调用模式、响应结构 |
| CRITICAL | 查询模式 | | 用于获取、过滤和遍历关联关系的GraphQL结构 |
| HIGH | 关联分析 | | 对多个查询返回的数据进行拼接、比对和推理 |
| HIGH | 报告输出 | | 呈现发现结果:摘要、表格、单对象详情、修复建议 |
| MEDIUM | 方案选择 | | 何时使用MCP分析、InfrahubCheck或Transform |
mcp__infrahub__infrahub_querymcp__infrahub__infrahub_list_schemamcp__infrahub__infrahub_getmcp__infrahub__infrahub_createmcp__infrahub__infrahub_updateundefinedmcp__infrahub__infrahub_querymcp__infrahub__infrahub_list_schemamcp__infrahub__infrahub_getmcp__infrahub__infrahub_createmcp__infrahub__infrahub_updateundefinedundefinedundefined1. Understand the question
→ "Which services depend on devices currently
in a maintenance window?"
2. Identify the node types involved
→ MaintenanceWindow, DcimDevice, Service
(or equivalent in your schema)
3. Query current state
→ mcp__infrahub__infrahub_query — one query
per node type, or combined
4. Correlate the data
→ Join across node types, filter, count, diff
5. Report findings
→ Summarize with counts, list affected objects,
suggest next steps1. Understand the question
→ "Which services depend on devices currently
in a maintenance window?"
2. Identify the node types involved
→ MaintenanceWindow, DcimDevice, Service
(or equivalent in your schema)
3. Query current state
→ mcp__infrahub__infrahub_query — one query
per node type, or combined
4. Correlate the data
→ Join across node types, filter, count, diff
5. Report findings
→ Summarize with counts, list affected objects,
suggest next steps