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io.github.AIops-tools/olvm-aiops

io.github.AIops-tools/olvm-aiops

Official

vm_capacity_summary

Read-only

Summarizes VM counts, configured vCPUs, host cores, and CPU assignment ratio for OLVM or oVirt engines without loading VM rows into context.

Instructions

[READ] Compact VM count, configured vCPUs, host cores and assignment ratio.

Walks VM pages inside the server; no VM rows enter the model context. A completed walk is not an atomic snapshot if the inventory changes during it. Missing CPU values, duplicate VM ids, or page/host limits make complete false and prevent unsupported totals.

Args: page_size: VM rows per engine request, 1-1000 (default 100). max_pages: Maximum VM pages to walk, 1-100 (default 100). target: Engine target name from config; omit to use the default.

Input Schema

NameRequiredDescriptionDefault
targetNo
max_pagesNo
page_sizeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.2

TDQS

A4.2/5.0
Behavior5/5

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

Beyond readOnlyHint=true, it discloses that the walk is page-by-page and non-atomic if inventory changes mid-walk, and that missing CPU values, duplicate VM ids or page/host limits force `complete=false` and suppress unsupported totals. These are real caveats an agent could not derive from the annotations or schema.

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?

Front-loaded with the outcome, then behavioral caveats, then parameters — good ordering with little waste. The Args block restates defaults already present in the schema, which is mild redundancy but aids scanning.

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?

With no output schema, the description correctly names the aggregate fields and the `complete` flag so the agent knows what comes back and when results are unreliable. It could be slightly more explicit about the exact return structure, but nothing needed to call it correctly is missing.

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?

Schema coverage is 0% — the schema carries only titles and defaults, with no bounds or meaning. The Args block supplies all three parameters' semantics, including the undocumented 1-1000 and 1-100 ranges and the "omit to use the default" behavior for target, so the description fully compensates.

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

Purpose4/5

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

The first line names a specific resource and output shape ("Compact VM count, configured vCPUs, host cores and assignment ratio"), which is clearly distinct from sibling listing tools like vm_list. The contrast is implicit rather than naming a specific sibling, so it stops short of a 5.

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

Usage Guidelines3/5

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

"Walks VM pages inside the server; no VM rows enter the model context" implies this is the choice when you want aggregates rather than per-VM detail, but the description never explicitly says when to prefer it over vm_list or vm_get. Usage is inferable but not stated.

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