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query_string_parse

Parse URL query string into key/value map (supports multi-values). When: Parse URL query strings into maps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Schema Changelog

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

  1. Added

TDQS

A3.9/5.0
Behavior3/5

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

No annotations provided, so description is the sole source. Mentions multi-value support, but lacks details on error handling, empty input, or encoding assumptions.

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 short, focused sentences with no redundant information. Every word is necessary.

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?

For a simple tool with one parameter and no output schema, the description covers the main purpose and multi-value support. However, it could be slightly clearer about the output format (e.g., map with array values for multi-value keys).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'query' has no schema description. The description implies input is a query string but adds no format details (e.g., leading '?', multiple values), leaving the agent to infer.

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?

Clearly states the action (parse), resource (URL query string), and output (key/value map). Also mentions multi-value support, distinguishing it from siblings like url_parse.

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?

Includes a 'When:' clause that explicitly indicates the use case. However, it does not specify when not to use it or mention alternative tools like url_parse.

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

B3/5.0
Disambiguation5/5

Every tool has a clear, distinct purpose with thorough descriptions. Even closely related tools like base64_decode/encode and hash_md5/sha256 are easily differentiated by name and description.

Naming Consistency5/5

All tools follow a consistent lowercase_underscore naming convention, typically in a <domain>_<action> or <action>_<domain> pattern. There are no jarring deviations or mixed styles.

Tool Count1/5

193 tools is an extreme count, far beyond what any focused server needs. While each tool has utility, the sheer number creates a kitchen-sink effect that overwhelms agents and hinders discoverability.

Completeness4/5

Within each subdomain (JSON, cron, JWT, etc.), the coverage is exhaustive, covering validation, conversion, parsing, and more. Minor gaps exist (e.g., YAML-to-TOML conversion missing), but overall it is remarkably complete.