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vmware-skills

io.github.zw008/vmware-debug

case_record_gap

Record missing evidence in a VMware investigation to keep the case accurate. Document what could not be obtained, why, and the next action to close the gap.

Instructions

[WRITE] Record something the investigation could NOT obtain.

WHEN: any time a fetch failed, was refused, returned nothing, or the data simply does not exist in this environment. This is the tool that keeps a case honest: an unrecorded gap makes it look better supported than it is.

RETURNS: {case_id, gap_id, grade, reasons}.

GOTCHAS: recording a gap does not punish the case for the evidence it does have — a missing confirmation caps the grade, it does not demote it. Writing gaps down is meant to be free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
whyYesWhy it could not be had — refused, unreachable, collected by nothing in this family, absent from this environment.
whatYesThe observation that could not be obtained — the thing you wanted, not the error you got.
blocksNoHypothesis ids (H1, H2, …) this gap holds up; they must already exist via case_hypotheses. Empty is fine.
case_idYesThe case this gap belongs to (from case_open/case_list).
how_to_closeYesThe next action that would close it, even outside this system ("open a vendor SR"). A gap with no stated next action reads like a to-do and gets skipped.
could_falsifyNoWould OBTAINING this be able to prove the hypothesis WRONG? false (default) is the ordinary case — missing corroboration, capping the case below Confirmed. true means it could overturn the hypothesis, holding it at Candidate.

Schema Changelog

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

  1. Addedv1.11.1

TDQS

A4.5/5.0
Behavior5/5

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

The description adds meaningful behavioral context beyond the annotations. It discloses the return shape {case_id, gap_id, grade, reasons} and the important grading effect: recording a gap caps the grade but does not demote it, and writing gaps down is 'meant to be free.' This is valuable non-obvious behavior.

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 compact, clearly sectioned with WHEN, RETURNS, and GOTCHAS, and every sentence carries useful information. The core purpose is front-loaded, and there is no redundant filler.

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?

The definition covers when to use the tool, what it returns, and the key behavioral gotchas about grade impact. The schema documents all parameters with strong descriptions, including how to reference existing hypotheses and what could_falsify means. No critical information appears missing for an agent to invoke this correctly.

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%, so the schema already documents each parameter well. The description provides general context for the tool's purpose but does not add specific meaning about individual parameters beyond what the schema already gives. Baseline 3 is appropriate.

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 and resource: 'Record something the investigation could NOT obtain.' It clearly distinguishes this from evidence-recording tools by emphasizing that the data was not obtainable, and the 'keeps a case honest' framing reinforces the unique purpose among siblings.

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?

The description gives an explicit WHEN section: 'any time a fetch failed, was refused, returned nothing, or the data simply does not exist in this environment.' It clearly communicates when to use the tool, though it does not explicitly name the alternative evidence-recording tool such as case_submit_evidence or state when not to use it.

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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