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vmware-skills

io.github.zw008/vmware-debug

by vmware-skills
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Python

case_readiness

Read-onlyIdempotent

Determine which evidence classes and symptom categories a VMware case can reach based on installed skills, revealing the investigation ceiling to avoid wasted effort.

Instructions

[READ] What strength of conclusion can this environment reach?

WHEN: before starting an investigation, or when a case will not go higher and you want to know whether that is fixable. Answering this first is worth far more than discovering it halfway through.

RETURNS: {classes, categories, unrecognised_skills, note}. A name that matched no skill in the catalogue comes back in unrecognised_skills rather than being absorbed into "not installed" — otherwise a typo reads as advice to install something you already have. Per evidence class: whether it is available, through which tools, and if not, how_to_supply. Per symptom category (storage, network, compute, ha_drs, configuration, accelerator, kubernetes, hardware, host_lifecycle, power_lifecycle, auth, platform, licensing, data_collection): a ceiling and the independent_sources behind it. There is deliberately no single score — "readiness 78%" cannot be acted on, "storage reaches Probable, hardware reaches Candidate" can.

GOTCHAS: two classes served by the SAME skill count as one source, so two available classes do not always mean Probable. The hardware class is unavailable no matter what is installed — nothing in this family reaches below ESXi — and the knowledge class becomes available only when entries are mounted under $OPS_HOME/knowledge/.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
available_skillsNoThe skills actually installed and configured, in either of the family's spellings — "monitor" and "vmware-monitor" name the same thing. Omit to assume all of them, which reports the ceiling imposed by the family itself rather than by this install. A name matching no catalogued skill comes back in `unrecognised_skills` rather than being read as "not installed".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.13.0
    • changedInput schema / title
      Previous value: -"_case_readiness_implArguments"New value: +"case_readinessArguments"
  2. Addedv1.11.1

TDQS

A4.7/5.0
Behavior5/5

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

The description goes well beyond the annotations by detailing the return object fields, the unrecognised_skills behavior, the deliberately absent single score, the same-skill-counts-as-one-source gotcha, and the hardware/knowledge class conditions. It also explains why the behavior exists (typo would otherwise read as 'not installed'), which is genuinely useful context.

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?

The description is well-structured with [READ], WHEN, RETURNS, and GOTCHAS sections, front-loading the purpose and usage before the detailed behavior. The length is justified by the absence of an output schema and the complexity of the edge cases, and every section earns its place.

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

Completeness5/5

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

With no output schema, the description carries the full burden of explaining return values and edge cases, and it does so thoroughly: object shape, per-class availability, per-category ceilings and independent sources, plus the critical gotchas. For a read-only analysis tool with one optional parameter, nothing an agent needs 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.

Parameters4/5

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

The schema already fully describes the single optional parameter at 100% coverage, so the baseline is 3. The description adds value by explaining that unmatched names surface in `unrecognised_skills` rather than being treated as 'not installed', and by clarifying that omission reports the family-intrinsic ceiling. This is meaningful extra semantics beyond the 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 opens with [READ] and frames the tool as assessing 'what strength of conclusion can this environment reach', which is a clear, specific purpose. It identifies the invocation context ('before starting an investigation') and the scope of the output, distinguishing it from the case_* siblings without needing to name them.

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?

An explicit WHEN block gives two concrete triggers: before starting an investigation, or when a case will not go higher and the agent wants to know if that is fixable. It does not explicitly name alternatives among the sibling tools, but the timing and purpose are clear enough to prevent obvious misuse.

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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