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johnmives

@revxl/devtools

by johnmives

regex

Test regex patterns against strings with match details, groups, and indices, and generate working code in JavaScript, Python, Go, Rust, and Java.

Instructions

Test a regex pattern against a string (with match details, groups, indices) and generate working code in JS/Python/Go/Rust/Java [PRO - 3 free trials]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
flagsNoRegex flags, e.g. 'gi' for global+case-insensitive (default: 'g')
patternYesRegular expression pattern (without delimiters)
languagesNoLanguages for code generation: javascript, python, go, rust, java (default: all)
test_stringNoString to test against (omit to just validate the pattern)
generate_codeNoGenerate code snippets in multiple languages (default: false)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.2

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It reveals useful behavioral details beyond the name: it returns match details/groups/indices, can generate code across languages, and flags a 'PRO - 3 free trials' limitation. This gives the agent important expectations about output richness and potential access restrictions.

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 a single, well-structured sentence that front-loads the core action, then adds output details, the code-generation capability, and the trial limitation. Every clause earns its place and there is no filler.

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?

The description, combined with a fully self-documenting input schema, is complete enough for an agent to select and invoke the tool correctly. It clarifies expected outputs (match details, groups, indices) and highlights a hard constraint ('3 free trials'). A dedicated output schema or explicit return-shape details would raise this further, but nothing critical is missing.

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 description coverage is 100%, so the schema already documents all five parameters and their meanings. The description adds little parameter-level detail beyond pointing to code-generation languages, which mirrors the existing 'languages' parameter. Baseline 3 is appropriate because the schema does the heavy lifting.

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 and resource: 'Test a regex pattern against a string' and also covers code generation. This clearly distinguishes it from the unrelated sibling dev-utility tools. The mention of match details, groups, and indices makes the tool's purpose concrete and recognizable.

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 implies a clear usage context: use this tool when you need to validate or test a regex against a string, inspect match groups/indices, or generate regex code across multiple languages. It does not explicitly name alternatives or exclusions, but no sibling tool offers a comparable regex-testing function, so the guidance is adequate.

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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