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Glama

TinyFn

get_email_pattern

Get regex pattern for email validation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
strictNoUse strict RFC 5322 pattern

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
formatNo
strictNo
countryNo
patternYes
versionNo
examplesNo
card_typeNo
descriptionNo
case_insensitiveNo
require_protocolNo
format_descriptionNo

Schema Changelog

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

  1. First observed

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations, the description carries the full burden for behavioral disclosure. It only states the action but does not describe the return format, what the regex pattern looks like, or how the 'strict' parameter alters the behavior. The output schema exists but is not detailed in the description.

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 sentence with no wasted words. It is appropriately sized for the tool's simplicity and front-loads the core purpose.

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

Completeness3/5

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

Given the tool's simplicity (one optional param, output schema exists), the description covers the basic purpose but lacks details like return type or the difference between strict and non-strict patterns. The presence of an output schema mitigates some need for explanation, but more context would improve completeness.

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% as the only parameter 'strict' is fully described in the schema ('Use strict RFC 5322 pattern'). The description adds no additional meaning beyond the schema, meeting the baseline for high coverage.

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 purpose: 'Get regex pattern for email validation.' It uses a specific verb ('get') and resource ('regex pattern for email validation'). This distinguishes it from siblings like 'validate_email' which performs validation, not pattern retrieval, and other pattern getters which target different formats.

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

Usage Guidelines2/5

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

No usage guidance is provided. The description does not indicate when to use this tool over alternatives (e.g., 'validate_email' or other pattern getters) or mention the optional 'strict' parameter's effect. The agent receives no context for selection.

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

C2.3/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as multiple random generators (random_integer, random_number), duplicate hashing functions (hash_md5, md5_checksum), and near-identical tools (compare, compare_2, compare_decimals). The sheer number of tools and lack of clear boundaries make it difficult for an agent to differentiate.

Naming Consistency1/5

Naming is highly inconsistent. There are duplicate tools with different names (camel_case vs to_camel_case, slug vs slugify), arbitrary suffixes like '_2', and mixing of patterns (e.g., generate_password vs password_entropy). No clear convention is followed.

Tool Count1/5

With 572 tools, the server is massively overpopulated for any coherent purpose. It includes trivial endpoints (true_endpoint, null, hello_world) and numerous duplicates, far exceeding a well-scoped utility set.

Completeness2/5

While the server covers many domains (math, strings, dates, colors, etc.), the presence of duplicate and trivial tools indicates a lack of thoughtful curation. There are gaps in basic operations (e.g., no dedicated file or network tools), and many tools are redundant.