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vmware-skills

io.github.zw008/vmware-debug

case_grade

Computes and records investigation's conclusion grade from the evidence ledger, returning direction, reasons, and ceiling. Finalize a case or capture status before handoff without setting the grade manually.

Instructions

[WRITE] Compute and record the conclusion grade — steps 07/08.

WHEN: when you think the investigation has reached a conclusion, or to record where it stands before handing it over.

There is deliberately NO parameter for the grade. You cannot state a conclusion level; it is recomputed from the ledger on every call. If you disagree with the result, change the ledger — submit the evidence that is missing, or record the gap that is blocking it.

The levels: Candidate (a hypothesis exists); Probable (at least two INDEPENDENT sources agree — two calls to the same skill are one source — and nothing outstanding could overturn it); Confirmed (that, plus a decisive item: a direct hardware diagnostic, a version-checked knowledge-base entry, or a vendor SR, and no gap left open); Excluded (an observation that actually rules the hypothesis out — "we looked and found nothing" is a gap, not an exclusion).

RETURNS: {grade, previous, direction, reasons, ceiling, ceiling_reasons, rules_source, rules_origin}. direction is initial/up/down/unchanged — grades may go DOWN, and the history records it when they do.

GOTCHAS: on a stock install ceiling is "probable", because Confirmed needs a decisive source and there is neither a hardware-diagnostic channel nor a knowledge library mounted yet. That is a real limit, not a caution. Every grading is appended to conclusion.md and none is ever rewritten.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
case_idYesThe case to grade (from case_open/case_list). This is the only parameter — see above for why there is no grade parameter.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 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 richly discloses behavior beyond the annotations: grades are recomputed, can go down, are appended to conclusion.md and never rewritten, and the default ceiling on a stock install is 'probable' with an explanation of why. This is exactly the kind of behavioral context that helps an agent predict side effects and limits.

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 longer than usual, but every section earns its place: WHEN, level definitions, RETURNS, and GOTCHAS. It is front-loaded with the core purpose and uses clear section markers, making it easy for an agent to scan and apply.

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 compensates by listing exact return fields, explaining the meaning of 'direction,' and documenting the practical ceiling limitation. It also tells the agent how to influence the grade (submit evidence or record a gap), covering the full decision loop around the call.

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 documents case_id clearly, and description coverage is 100%, so the baseline is solid. The description adds meaningful context by explaining why there is deliberately no grade parameter and that the grade is derived from the ledger, which prevents an agent from expecting a grade input.

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 a specific verb-resource pair: 'Compute and record the conclusion grade — steps 07/08.' It also clarifies a distinguishing design point (no grade parameter; recomputed from ledger) and defines the grade levels, making the tool's purpose unmistakable relative to siblings like case_readiness or case_close.

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?

It provides an explicit WHEN section: 'when you think the investigation has reached a conclusion, or to record where it stands before handing it over.' It does not explicitly name sibling alternatives or say when not to use it, but the condition is clear and actionable.

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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