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natl-set

ANTLR4 MCP Server

by natl-set

generate-stress-test

Generate stress test inputs to evaluate grammar performance and robustness using nested, wide, or repetition strategies. Identify bottlenecks and benchmark behavior under extreme input patterns.

Instructions

Generate stress test inputs for grammar performance testing.

When to use: Testing grammar robustness, identifying performance issues, benchmarking.

Generation strategies:

  • nested: Deep nesting of recursive rules (tests stack depth)

  • wide: Many alternatives in choice rules (tests branching)

  • repetition: Repeated sequences (tests loops)

  • mixed: Combination of all strategies (default)

Parameters:

  • grammar_content: The grammar to generate tests for

  • strategy: Generation strategy (nested, wide, repetition, mixed)

  • depth: Nesting depth for nested strategy (default: 50)

  • count: Number of alternatives for wide strategy (default: 100)

  • repetitions: Repetition count for repetition strategy (default: 100)

Returns:

  • Generated test input

  • Expected characteristics (depth, width, size)

  • Warnings if grammar structure can't support requested strategy

Example: grammar_content: "grammar Expr; ..." strategy: "nested" depth: 30

Output: "(((...(1 + 2)...)))" (30 levels deep)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of alternatives for wide strategy (default: 100)
depthNoNesting depth for nested strategy (default: 50)
strategyNoGeneration strategy (default: mixed)
from_fileNoOptional: path to a grammar file to read
repetitionsNoRepetition count for repetition strategy (default: 100)
grammar_contentNoThe ANTLR4 grammar file content
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses generation strategies, expected returns, and that warnings are produced if the grammar can't support a strategy. It does not mention potential performance/resource implications of stress testing or side effects, but the core behavior is well-covered.

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 well-organized with clear sections (When to use, Generation strategies, Parameters, Returns, Example). Each section adds value: the example illustrates usage, the strategy list clarifies options, and the returns section sets expectations. No fluff.

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 6 parameters and no output schema, the description covers most essentials: strategies, returns, example. It misses mentioning 'from_file' in the parameter list, but the schema covers it. The example and returns section help complete the picture, slightly imperfect but adequate.

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 coverage is 100%, so baseline is 3. The description repeats parameter names and defaults, adding minimal extra meaning. It also omits 'from_file' from the parameter list, but the schema describes it. No additional syntax or semantics beyond schema.

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 starts with 'Generate stress test inputs for grammar performance testing' - a specific verb and resource, clearly distinguishing it from sibling tools like test-parser-rule or benchmark-parsing. The scope is well-defined.

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?

An explicit 'When to use' section states: 'Testing grammar robustness, identifying performance issues, benchmarking.' This gives clear context. However, it does not mention when not to use or compare with alternatives, so a deduction from 5.

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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