JMeter

Lint JMX Test Plan Snippet

lint_jmx_snippet

Validate a JMeter test plan XML string or snippet against best practices and performance anti-patterns, and return a structural inventory with thread groups, sampler/listener/assertion counts, HTTP Defaults/Header/Cookie/CSV presence, plugin classes, and JMeter version.

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": {
      "jmxContent": "<jmxContent>"
    },
    "name": "lint_jmx_snippet"
  }
}

Input Schema

Name	Required	Description	Default
`jmxContent`	Yes	JMX XML string or test plan snippet to analyze (max 1MB).

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedSep 27, 2026

changedInput schema / properties / jmxContent / description

Previous value: -"JMX XML string or test plan snippet to analyze."New value: +"JMX XML string or test plan snippet to analyze (max 1MB)."

addedInput schema / properties / jmxContent / maxLength
```
Added value: +1000000
```

First observedAug 21, 2026

TDQS

A3.5/5.0

Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It does disclose the analysis outputs it produces (thread groups, sampler/listener/assertion counts, HTTP Defaults/Header/Cookie/CSV presence, plugin classes, JMeter version), which is useful. However, it never states that the operation is non-mutating, how it behaves on malformed XML, or whether findings are returned as errors versus a report, leaving meaningful gaps.

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?

It is a single dense sentence with the verb and resource front-loaded and no filler. The long inventory clause is informative rather than wasted, though the sentence is packed enough that it could be split for readability.

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

Completeness4/5

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 enumerating the structural inventory returned, which is exactly what the agent needs to know about results. It falls short only on failure behavior and the shape of the validation findings, which a lint tool's caller would want.

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?

There is one parameter with 100% schema description coverage, including the 1MB max and non-empty constraints, so the schema does the heavy lifting. The description only restates 'XML string or snippet' without adding format or encoding guidance, so baseline 3 applies.

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 states a specific verb (validate/lint) and resource (JMeter test plan XML string or snippet), and enumerates the analysis dimensions it checks (best practices, performance anti-patterns). This clearly distinguishes it from siblings like lint_groovy_script and convert_curl_or_har_to_jmx, which operate on different inputs.

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 never states when to reach for this tool versus alternatives such as convert_* tools or lookup_error_playbook, nor does it give prerequisites (e.g., 'use before running a test plan' or 'after converting a HAR'). Usage is only inferable from the verb 'validate', which is minimal guidance.

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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