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test_regex

Test a regex pattern against an input string.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
flagsNoRegex flags (g, i, m, s, u, y)
inputYesInput string to test against
patternYesRegular expression pattern

Schema Changelog

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

  1. First observed

TDQS

B3.2/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states that the tool 'tests' a regex, but does not mention side effects, return value, handling of invalid patterns, or effects of flags. The agent cannot anticipate what the tool actually returns or does beyond the verb.

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 concise sentence with no wasted words. It is front-loaded and directly communicates the tool's purpose without any superfluous content.

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

Completeness2/5

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

The tool is simple, but with no output schema and no annotation context, the description must clarify behavior. It does not state what the tool returns (e.g., a boolean, matched substrings, or errors). This gap makes the description insufficient for an agent to fully understand the tool's behavior.

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 input schema provides complete descriptions for all three parameters (pattern, input, flags), achieving 100% schema coverage. The description adds no additional parameter meaning beyond what the schema already documents, so the baseline score of 3 is appropriate.

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 action: 'Test a regex pattern against an input string.' This specific verb and resource combination makes the purpose unambiguous and distinct from sibling tools like convert_currency or validate_nif.

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 purpose statement implies usage for regex testing, but there is no explicit guidance on when to use this tool versus alternatives or when not to use it. The sibling tools are mostly unrelated, so no exclusion is needed, but the description does not provide any contextual usage direction.

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

A3.5/5.0
Disambiguation5/5

Each tool has a distinct purpose and target resource or operation. While some tools are thematically related (e.g., detect_secrets and classify_gdpr both analyze text), their specific outputs and use cases are clearly separated by names and descriptions.

Naming Consistency4/5

Most tools follow a clear verb_noun pattern (convert_currency, generate_uuid, validate_iban), and the noun_to_noun conversion tools (csv_to_json, html_to_text) form a consistent sub-pattern. The mix of verb_noun and X_to_Y is understandable and predictable, though not uniform.

Tool Count3/5

23 tools is on the higher end for a utility server, feeling like a grab-bag of many unrelated functions. While each tool is simple and serves a purpose, the count exceeds the typical well-scoped range, making it heavier than ideal.

Completeness3/5

The tool coverage is broad but scattered with no clear domain focus. Obvious complementary utilities are missing, such as URL encoding/decoding, YAML conversion, or PDF generation. However, within each small category, core operations are present, so agents can work around gaps.

Resources