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Regex Tester

test_regex
Read-onlyIdempotent

Run a JavaScript regular expression against a test string using a real regex engine. Returns all matches with capture groups and indices.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe text to run the expression against
flagsNoRegex flags such as g, i, m, s, u (default g)g
patternYesJavaScript regular expression source, without the slashes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of items
resultNoThe result, when it is not an object
matchesNo

Schema Changelog

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

  1. Changed4 schema fields changed
    • addedInput schema / properties / flags / description
      Added value: +"Regex flags such as g, i, m, s, u (default g)"
    • addedInput schema / properties / pattern / description
      Added value: +"JavaScript regular expression source, without the slashes"
    • addedInput schema / properties / text / description
      Added value: +"The text to run the expression against"
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "https://json-schema.org/draft/2020-12/schema",
      +  "additionalProperties": {},
      +  "properties": {
      +    "count": {
      +      "description": "Number of items",
      +      "type": "number"
      +    },
      +    "matches": {
      +      "items": {},
      +      "type": "array"
      +    },
      +    "result": {
      +      "description": "The result, when it is not an object"
      +    }
      +  },
      +  "type": "object"
      +}
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover safety with readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context by noting it runs 'using a real regex engine' and returns 'all matches with capture groups and indices.' There is no contradiction with the annotations.

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?

Two sentences, front-loaded with the tool's purpose and followed by the key output behavior. Every phrase earns its place; 'real regex engine' adds important execution semantics without padding.

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

Completeness5/5

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

For a simple three-parameter utility with full schema descriptions, an output schema, and safety annotations, the description is complete enough for correct invocation. Invalid-regex behavior is not described, but the output schema and real-engine semantics make this a minor omission, not a blocker.

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 the schema already documents pattern, text, and flags, including the default 'g' flag and the 'without the slashes' constraint. The description adds little new parameter-level meaning, but it does not need to because the schema carries that load.

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?

Description states a specific verb, resource, and scope: 'Run a JavaScript regular expression against a test string using a real regex engine.' It also clearly specifies the observable result: 'Returns all matches with capture groups and indices.' Although it does not explicitly name a sibling, no sibling tool is a regex tester, so it is clearly differentiated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to prefer this tool over alternatives or give any exclusions. The 'real regex engine' wording implies it is for validating actual JS regex behavior, but that guidance is implicit. A sentence routing an agent to this tool versus similar utilities would improve it.

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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TDQS

A3.8/5.0
Disambiguation5/5

Every tool targets a distinct resource or action, and the detailed descriptions clearly separate near neighbors like generate_test_bsn versus generate_brp_test_data, read_page versus url_screenshot versus url_to_pdf, and image_compress/convert/resize. Even with 40 tools, there is no real boundary-blurring overlap.

Naming Consistency3/5

All names are snake_case and readable, but the set mixes conventions: verb_noun (generate_*, validate_*), noun_verb (pdf_merge, image_resize), conversion-style names (csv_to_json, html_to_pdf), and bare nouns (base64, qr_code_png). The groups are recognizable, but there is no single predictable pattern.

Tool Count2/5

Forty tools is an oversized surface for an agent to consider on every call, well above the point where tool selection cost starts to hurt. The broad purpose explains the count, but many one-off utilities could be grouped or exposed selectively.

Completeness3/5

The server covers many domains—encoding, Dutch test data, image/PDF handling, memory, and workflows—but several categories are partial: there are no reverse conversions like json_to_csv or html_to_markdown, no PDF text extraction, and no workflow create/update/delete tools. Agents can work around some gaps, but notable operations are missing.

Resources