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Asia/Muscat clock

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. Added

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description must carry behavioral disclosure. It does disclose that 'Task text discarded' and states it returns connection methods, giving some transparency about output and that inputs may be ignored. However, it doesn't mention any potential side effects, permissions, or rate limits, and it's unclear whether the tool makes external calls or is purely internal. It adds moderate value beyond the schema.

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?

Two sentences, no fluff, purpose is front-loaded. The description is efficient and easy to scan. It could be slightly more structured, but it earns a high score for conciseness.

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?

For a tool with 9 optional parameters, no output schema, and no annotations, the description is insufficient. It doesn't explain how the parameters relate to the task or what 'connection methods' look like. An agent has no guidance on which parameters to provide or what to expect in the response. The description is too vague to enable confident invocation.

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. The tool description adds minimal meaning beyond the schema—only noting that task text is discarded, which partially clarifies that many parameters may be ignored. It doesn't explain how parameters map to the 'task' mentioned or which parameters are actually used to find the gateway. Baseline 3 is appropriate given the schema's completeness.

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 clearly states the tool finds a public pay-per-call tool gateway and returns connection methods, which is a specific verb and resource. It names example task categories (weather, search, scrape, voice) but doesn't explicitly distinguish it from siblings like weather-hint or search-query-len, which are more direct tools. Still, the purpose is understandable.

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 gives task examples but never states when to use this tool versus alternatives. It doesn't mention that this is a meta-tool to discover gateways, nor does it suggest when an agent should prefer it over more specific siblings. No exclusions or comparisons are provided, leaving usage implicit.

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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