Nutanix AIops

lcm_precheck

Destructive

Run read-safe prechecks on cluster entities to validate readiness for LCM upgrades, ensuring compatibility and safe lifecycle operations.

Instructions

[WRITE][risk=medium] Run LCM prechecks for entities on a cluster (read-safe validation).

Args:
    cluster_ext_id: Cluster extId as returned by cluster_list.
    entity_ext_ids: LCM entity extIds (from lcm_inventory) to precheck.
    target: Prism Central target name from config; omit for the default.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "cluster_ext_id": "<cluster_ext_id>",
      "entity_ext_ids": "<entity_ext_ids>"
    },
    "name": "lcm_precheck"
  }
}

Input Schema

Name	Required	Description	Default
`target`	No
`cluster_ext_id`	Yes
`entity_ext_ids`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 28, 2026

TDQS

B3.1/5.0

Behavior1/5

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

The description labels this a 'read-safe validation', implying no state change, while the annotations declare destructiveHint=true and readOnlyHint=false. These directly conflict, so an agent cannot tell whether the call mutates the cluster. This is an Annotation Contradiction.

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

Conciseness5/5

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

Front-loads the operation tag and purpose, then a tight Args block with one line per parameter. No filler; every line earns its place.

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

Completeness2/5

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

For a validation tool with no output schema, the description never explains what a precheck returns or what the agent should do with the result (pass/fail, blocking errors). Combined with the read-safe/destructive contradiction and absent success criteria, it leaves an agent unable to interpret the outcome correctly.

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

Parameters4/5

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

With 0% schema description coverage, the description carries the full burden and largely meets it: it names each of the three parameters and gives provenance (cluster_list, lcm_inventory, config) plus the default behavior for target. It stops short of clarifying whether entity_ext_ids accepts mixed entity types or how many, but it meaningfully compensates for the schema gap.

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?

States a specific verb and resource: 'Run LCM prechecks for entities on a cluster'. It distinguishes itself from the sibling lcm_inventory (source of entity_ext_ids) and cluster_list (source of cluster_ext_id), so an agent can place it in the LCM workflow. It does not, however, contrast with lcm_update or explain how precheck relates to the actual update.

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?

Usage is implied by the provenance hints ('from lcm_inventory', 'as returned by cluster_list'), which tell the agent where the inputs come from. But there is no explicit when-to-use guidance, no statement that this should precede lcm_update, and no exclusions or prerequisites. The context 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.