lmiranda
a74a048898
Add validation hooks, best practices skill, and new commands to enforce NetBox data quality standards: Hooks: - SessionStart: Test NetBox connectivity, report data quality issues - PreToolUse: Validate VM/device parameters before create/update New Commands: - /cmdb-audit: Data quality analysis (vms, devices, naming, roles) - /cmdb-register: Register current machine with running applications - /cmdb-sync: Sync machine state with NetBox, detect drift Best Practices Skill: - Dependency order (regions -> sites -> devices -> VMs) - Site/tenant/platform assignment requirements - Naming conventions enforcement - Role consolidation guidance Updated agent with validation requirements, dependency order checks, naming convention warnings, and duplicate prevention. Marketplace: 5.0.0 -> 5.1.0 Plugin: 1.0.0 -> 1.1.0 Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
5.0 KiB
5.0 KiB
description
| description |
|---|
| Audit NetBox data quality and identify consistency issues |
CMDB Data Quality Audit
Analyze NetBox data for quality issues and best practice violations.
Usage
/cmdb-audit [scope]
Scopes:
all(default) - Full audit across all categoriesvms- Virtual machines onlydevices- Physical devices onlynaming- Naming convention analysisroles- Role fragmentation analysis
Instructions
You are a data quality auditor for NetBox. Your job is to identify consistency issues and best practice violations.
IMPORTANT: Load the netbox-patterns skill for best practice reference.
Phase 1: Data Collection
Run these MCP tool calls to gather data for analysis:
1. virt_list_vms (no filters - get all)
2. dcim_list_devices (no filters - get all)
3. virt_list_clusters (no filters)
4. dcim_list_sites
5. tenancy_list_tenants
6. dcim_list_device_roles
7. dcim_list_platforms
Store the results for analysis.
Phase 2: Quality Checks
Analyze collected data for these issues by severity:
CRITICAL Issues (must fix immediately)
| Check | Detection |
|---|---|
| VMs without cluster | cluster field is null AND site field is null |
| Devices without site | site field is null |
| Active devices without primary IP | status=active AND primary_ip4 is null AND primary_ip6 is null |
HIGH Issues (should fix soon)
| Check | Detection |
|---|---|
| VMs without site | VM has no site (neither direct nor via cluster.site) |
| VMs without tenant | tenant field is null |
| Devices without platform | platform field is null |
| Clusters not scoped to site | site field is null on cluster |
| VMs without role | role field is null |
MEDIUM Issues (plan to address)
| Check | Detection |
|---|---|
| Inconsistent naming | Names don't match patterns: devices={role}-{site}-{num}, VMs={env}-{app}-{num} |
| Role fragmentation | More than 10 device roles with <3 assignments each |
| Missing tags on production | Active resources without any tags |
| Mixed naming separators | Some names use _, others use - |
LOW Issues (informational)
| Check | Detection |
|---|---|
| Docker containers as VMs | Cluster type is "Docker Compose" - document this modeling choice |
| VMs without description | description field is empty |
| Sites without physical address | physical_address is empty |
| Devices without serial | serial field is empty |
Phase 3: Naming Convention Analysis
For naming scope, analyze patterns:
- Extract naming patterns from existing objects
- Identify dominant patterns (most common conventions)
- Flag outliers that don't match dominant patterns
- Suggest standardization based on best practices
Expected Patterns:
- Devices:
{role}-{location}-{number}(e.g.,web-dc1-01) - VMs:
{prefix}_{service}or{env}-{app}-{number}(e.g.,prod-api-01) - Clusters:
{site}-{type}(e.g.,home-docker)
Phase 4: Role Analysis
For roles scope, analyze fragmentation:
- List all device roles with assignment counts
- Identify single-use roles (only 1 device/VM)
- Identify similar roles that could be consolidated
- Suggest consolidation based on patterns
Red Flags:
- More than 15 highly specific roles
- Roles with technology in name (use platform instead)
- Roles that duplicate functionality
Phase 5: Report Generation
Present findings in this structure:
## CMDB Data Quality Audit Report
**Generated:** [timestamp]
**Scope:** [scope parameter]
### Summary
| Metric | Count |
|--------|-------|
| Total VMs | X |
| Total Devices | Y |
| Total Clusters | Z |
| **Total Issues** | **N** |
| Severity | Count |
|----------|-------|
| Critical | A |
| High | B |
| Medium | C |
| Low | D |
### Critical Issues
[List each with specific object names and IDs]
**Example:**
- VM `HotServ` (ID: 1) - No cluster or site assignment
- Device `server-01` (ID: 5) - No site assignment
### High Issues
[List each with specific object names]
### Medium Issues
[Grouped by category with counts]
### Recommendations
1. **[Most impactful fix]** - affects N objects
2. **[Second priority]** - affects M objects
...
### Quick Fixes
Commands to fix common issues:
Assign site to VM
virt_update_vm id=X site=Y
Assign platform to device
dcim_update_device id=X platform=Y
### Next Steps
- Run `/cmdb-register` to properly register new machines
- Use `/cmdb-sync` to update existing registrations
- Consider bulk updates via NetBox web UI for >10 items
Scope-Specific Instructions
For vms scope:
Focus only on Virtual Machine checks. Skip device and role analysis.
For devices scope:
Focus only on Device checks. Skip VM and cluster analysis.
For naming scope:
Focus on naming convention analysis across all objects. Generate detailed pattern report.
For roles scope:
Focus on role fragmentation analysis. Generate consolidation recommendations.
User Request
$ARGUMENTS