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vmware-skills

io.github.zw008/vmware-debug

case_get

Read-onlyIdempotent

Retrieve a VMware investigation case's scope, evidence counts, and grade history to understand why it holds its current grade and identify blocking gaps.

Instructions

[READ] One case: its scope, its ledger sizes, and its grade history.

WHEN: to pick up an investigation, or to see why a case sits at the grade it does. Returns counts and identifiers rather than the whole ledger — read the case folder itself (the path from case_open) for full evidence bodies.

RETURNS: {case_id, path, state, grade, opened_at, scope, evidence_count, sources, gap_count, blocking_gaps, grade_history}. sources is the distinct skills evidence came from, which is what corroboration is counted in.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
case_idYesThe case id returned by case_open, or listed by case_list. An unknown id is an error, never an empty case.

Schema Changelog

Changes observed during successful MCP inspections.

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

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context by stating that it returns aggregate counts and identifiers rather than full evidence bodies, and by listing exactly what fields are returned, including grade_history and blocking_gaps.

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 tightly structured with READ/WHEN/RETURNS sections, front-loading the core purpose and use case. Every sentence adds value, and the return field list is provided in a compact, scannable format without unnecessary prose.

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?

For a one-parameter, read-only tool with rich annotations and no output schema, this description is complete. It explains what the tool returns, when to use it, and when to use an alternative, so an agent can correctly select and invoke it without additional context.

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

Parameters3/5

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

Schema description coverage is 100%, and the single parameter case_id is well documented in the schema, including the note that an unknown id is an error. The description does not add extra parameter semantics beyond the schema, which is acceptable given full schema coverage.

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] One case' and immediately scopes the tool: 'its scope, its ledger sizes, and its grade history.' It clearly distinguishes itself from sibling tools by noting that it returns counts and identifiers rather than the whole ledger, so an agent can tell this apart from case_open, case_list, or case_timeline.

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

Usage Guidelines5/5

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

The 'WHEN' section gives explicit use cases: 'to pick up an investigation, or to see why a case sits at the grade it does.' It also provides a when-not and alternative: 'read the case folder itself (the path from case_open) for full evidence bodies,' which tells the agent exactly when case_get is insufficient.

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