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Find a public pay-per-call tool gateway for a task such as weather, search, scrape, or voice. Returns connection methods. Task text discarded.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refNoGit ref name; discarded after the shape check
urlNoHTTPS URL to normalize or cite
cityNoCity name for a public weather hint; discarded after the call
feedNoPublic RSS or Atom URL; titles discarded
hostNoPublic hostname
jsonNoJSON text to validate; discarded after the check
pathNoFile path to check; no disk access
zoneNoIANA timezone name
queryNoSearch text; discarded after the length check

Schema Changelog

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

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. It does disclose that 'Task text is discarded.' and that the tool 'Returns connection methods,' which suggests a read-only catalog lookup. However, it does not explain whether the call is network-bound, whether using a returned gateway has cost implications, or what failure/response behavior looks like.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded with the tool's purpose and use cases, making it efficient. The phrase 'Task text discarded.' is somewhat ambiguous given there is no task-text parameter in the schema, which keeps this from being a perfect 5.

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?

Despite a rich 9-parameter schema with per-parameter descriptions, the tool has no output schema, no annotations, and a task-finding job that is underspecified for an agent. It never explains how to map a task like 'voice' or 'scrape' onto the listed parameters (host, feed, json, path, zone), nor what 'connection methods' actually contains, leaving a substantial invocation gap.

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 every parameter, yielding a baseline of 3. The description's mapped task categories ('weather, search, scrape, voice') loosely hint at which parameter groups matter, but it does not explicitly tie parameters to the advertised tasks or add further semantics.

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: 'Find a public pay-per-call tool gateway,' with concrete example tasks ('weather, search, scrape, or voice'). This clearly distinguishes the tool from the narrower sibling utilities (e.g., weather-hint, timezone, normalize-url), which operate on single domains. The added 'Task text discarded' detail also sharpens the tool's scope.

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 implies when to use the tool through examples ('for a task such as weather, search, scrape, or voice'), but it does not explicitly state alternatives or when not to use this tool versus the sibling utilities. No exclusions or comparison routes are given, so guidance is left mostly to inference.

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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