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zw008

VMware-Monitor

vm_investigation_bundle

Read-onlyIdempotent

Correlates VM state, host, cluster, datastores, snapshots, alarms, performance, and recent events into a single drill-down view for rapid troubleshooting.

Instructions

[READ] "What is happening around this VM?" — one correlated drill-down.

Collects and correlates everything around a single VM so you don't stitch get_vm_info + list_snapshots + get_alarms + get_vm_performance + get_recent_events yourself (which a smaller model often mis-orders): the VM's state, the host it runs on, its cluster context, the datastores backing it, its snapshots and triggered alarms, live performance, and a merged event timeline correlating recent events from the VM, host, cluster and datastores (newest first). All cross-object reads are batched — cheap even on large fleets. Aggregation happens in the tool; explain the result in operational language, do not dump it raw.

Use this AFTER cluster_health_summary points at a problem VM, or whenever the operator asks "what's going on with ?". Point-in-time snapshot — no trending.

Args: vm_name: Exact VM name. Unknown names return a teaching error naming how to list VMs. Get the name from list_vms or cluster_health_summary first. target: Optional vCenter/ESXi target name from config (default target if omitted). hours: Event-timeline look-back window in hours (default 24).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hoursNo
targetNo
vm_nameYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Description adds that reads are batched, cheap on large fleets, and aggregation happens inside the tool, going beyond annotations. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is somewhat lengthy but front-loaded with a clear purpose. Each paragraph adds value: functionality, usage guidance, parameters. Could be slightly more concise but well-organized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and complex output, the description covers inputs, behavior, aggregation, non-trending nature, and relationship to other tools. Adequately complete for an investigative bundle.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema coverage, description fully explains each parameter: vm_name (exact name, error handling, source), target (optional, default), hours (look-back window, default 24). Adds critical context missing from schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it collects and correlates everything around a single VM, listing specific data points (state, host, cluster, datastores, snapshots, alarms, performance, event timeline). It distinguishes itself from stitching multiple separate calls.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly suggests using after cluster_health_summary points to a problem VM or when asked 'what's going on with <vm>?'. Notes it's a point-in-time snapshot, not for trending. Could specify when NOT to use, but the guidance is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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