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Quoted-printable length, input discarded

agent-tool-index

Find a public pay-per-call tool gateway (Monid). Returns CLI setup, how-it-works, skill file, and remote MCP hops. 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

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It only mentions that task text is discarded and that it returns connection methods. It doesn't disclose whether external calls are made, potential rate limits, auth requirements, or the exact nature of the returned methods. This is minimal and leaves important operational traits unstated.

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 two concise sentences with no filler. The purpose is front-loaded and the key behavioral note (task text discarded) is included. It is appropriately sized for the tool's scope.

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 having 9 optional parameters and no output schema or annotations, the description does not clarify how to construct a task (e.g., which parameter maps to which task type) or what the returned connection methods look like. It leaves critical details about input usage and output format unexplained, making it inadequate for an agent to invoke correctly without further inference.

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 each parameter already has a description including 'discarded after the call' or similar. The main description adds the context that these parameters form a 'task' and that the tool finds a gateway, but this is marginal. Since the schema does the heavy lifting, a baseline of 3 is appropriate; the description doesn't materially enhance parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific purpose: find a pay-per-call tool gateway for a task, and returns connection methods. It gives example tasks (weather, search, scrape, voice), making the intent clear. However, it doesn't explicitly contrast with sibling tools like weather-hint or search-query-len, though the meta nature is apparent.

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?

The description does not provide any explicit guidance on when to use this tool versus the many sibling tools. It implies usage when a gateway is needed, but does not state when not to use it or name alternatives. An agent would have to infer which tool is appropriate based on the task.

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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