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Kratos MCP Server

results_compare

Compare two result sets for the same variable at matching physical times, using absolute and relative tolerances to detect differences without interpolation.

Instructions

Compare histories or matching-mesh fields at matching physical times without interpolation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
atolNo
modeNofield
rtolNo
pointNo
csv_fileNo
variableYes
candidateYes
referenceYes
time_atolNo
associationNopoint
entity_indexNo
candidate_seriesNo
reference_seriesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.5.0

TDQS

C2.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions one key trait—'without interpolation'—and implies that comparisons happen only at matching physical times. However, it does not disclose how mismatches are handled, what tolerances are used (atol, rtol, time_atol), whether the operation is read-only, or what the output looks like. For a tool with 13 parameters, this is insufficient behavioral context.

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

Conciseness3/5

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

The description is a single sentence and is efficient in wording, but it is too brief for the tool's complexity. It conveys the core idea but omits crucial context. Conciseness is achieved, but at the cost of completeness. The sentence is front-loaded with the main action, but there is no elaboration on scope or edge cases.

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

Completeness1/5

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

For a tool with 13 parameters, zero schema descriptions, and no annotations, the description is severely inadequate. It does not explain the return format (despite an output schema), the meaning of key parameters, how tolerances are applied, or any limitations. An agent cannot confidently invoke this tool correctly based on the current description alone.

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

Parameters1/5

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

The schema description coverage is 0%, meaning the schema provides no parameter descriptions. The description adds nothing about any of the 13 parameters—it does not explain what 'reference', 'candidate', 'variable', or the various tolerances mean. Since the schema is silent, the description should compensate but does not, leaving the agent with no parameter-level guidance.

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?

The description states a clear verb 'compare' and specifies the resources: histories or matching-mesh fields, and the condition 'at matching physical times without interpolation'. This distinguishes it from sibling tools like results_time_history or results_probe, though it does not explicitly name an alternative. The purpose is clear and specific, but it could better differentiate itself by naming a sibling.

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

Usage Guidelines2/5

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

The description offers no guidance on when to use this tool versus alternatives. It does not state typical use cases, prerequisites, or when not to use it. The only implied context is that it is for comparison, but there is no explicit direction for an agent choosing between this and other results-related tools.

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