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perfsage-jmeter-mcp

by perfsage

edit_jmx

Apply structured edits to an existing JMeter JMX plan using operations like set_workload, change_method, or add_jsr223, then write a new file. Returns the path, summary, and next action.

Instructions

Apply structured edits to an existing JMX plan and write a new file.

Use after generate_jmx (or with a hand-written single-ThreadGroup plan). The LLM translates natural-language asks into operations such as set_workload (fixed/ramp/stress/burst), change_method, wrap_loop, wrap_while, and add_jsr223. Writes a new plan by default; set overwrite=true only to replace plan_path. Returns path, summary, ops_applied, and next_action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
overwriteNo
plan_pathYes
operationsYes
output_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses critical behavioral traits: 'Writes a new plan by default; set overwrite=true only to replace plan_path' and lists return values ('Returns path, summary, ops_applied, and next_action'). This is adequate transparency for a mutation tool, though it stops short of covering error cases or permissions.

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 and thoroughly front-loaded. The opening sentence states the core purpose, followed by usage context, operation examples, default behavior, and return values. Every sentence adds information without redundancy, making it an exemplary model of conciseness.

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?

Given the tool's moderate complexity, lack of annotations, and presence of an output schema, the description covers the essential aspects: when to use, what to provide, and what to expect in return. It could enrich the details of individual operations, but the provided information is sufficient for an agent to decide and invoke it 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?

The schema has 0% description coverage, so the description must compensate. It explains the overwrite parameter's purpose and gives examples of operations (e.g., set_workload with fixed/ramp/stress/burst). However, plan_path and output_path are only superficially referenced, and the nested operation parameters are not detailed beyond the op enum list.

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 clearly states the tool's function: 'Apply structured edits to an existing JMX plan and write a new file.' It uses a specific verb and resource, and lists example operations, making its purpose unambiguous. It also distinguishes itself from the sibling generate_jmx by explicitly positioning itself as the follow-up editing step.

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 provides explicit usage context: 'Use after generate_jmx (or with a hand-written single-ThreadGroup plan).' This tells the agent when to use the tool and what inputs are appropriate. It doesn't explicitly list alternatives or exclusions, but the given context 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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