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EvalKit MCP Server

EvalKit MCP Server

by tr4m0ryp
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

eval_decompose_query

Splits a query into topic-based conceptual sub-components for granular analysis.

Instructions

Split a query into conceptual sub-components for analysis.

Divides the input into constituent parts based on topic boundaries.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "eval_decompose_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYes
max_piecesNo
auto_splitNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

C2.6/5.0
Behavior2/5

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

With no annotations provided, the description must fully disclose behavioral traits. It only states that the query is split into parts based on topic boundaries. It does not mention side effects, whether the operation is read-only, how the splitting algorithm works, or any constraints. This is insufficient for a behavioral understanding.

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

Conciseness4/5

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

The description is concise at two sentences, with no redundant information. The first sentence states the core purpose, and the second adds detail. It is front-loaded and efficient, though some might argue it is too brief given the missing parameter details.

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

Completeness2/5

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

Given the presence of an output schema (not shown), the description does not need to explain return values, but it still lacks information about parameters, usage context, and behavioral traits. The tool has three parameters with no description, which makes it incomplete for effective use.

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 has 0% description coverage for parameters, so the description must compensate. However, the description does not mention any of the three parameters (query, max_pieces, auto_split) or their semantics. It only describes the high-level function, providing no meaning beyond the parameter names in the schema.

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 clearly states the tool splits a query into conceptual sub-components based on topic boundaries. It is specific about the action and resource, and while it doesn't explicitly differentiate from siblings, the sibling tools have distinct purposes (robustness, evasion, status), so confusion is unlikely.

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, contexts, or scenarios where the tool is appropriate or inappropriate. The description lacks any exclusions or alternative tool names.

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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