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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

A3.5/5.0
Behavior3/5

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

There are no annotations, so the description must carry the behavioral transparency burden. It does disclose that the tool returns CLI setup, how-it-works, skill file, and remote MCP hops, and that task text is discarded, which signals a read-only, non-persistent behavior. It does not mention potential costs, rate limits, network access, or authentication, but for a discovery tool the disclosed behavior is at least partially sufficient.

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 one dense, front-loaded sentence with no filler. It states the purpose first, then the return contents, then the key discard behavior. Every clause earns its place.

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?

With 9 optional parameters, no output schema, and no annotations, the description gives a useful high-level picture of the return items but does not explain how to choose or omit parameters, nor what the returned CLI setup or MCP hops look like. It is adequate for a simple discovery tool, but not fully complete for an agent deciding how to invoke it.

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?

The input schema has 100% description coverage, and each parameter already explains its own role and whether it is discarded. The description adds only a high-level note that 'Task text discarded', which loosely maps to the query parameter but does not meaningfully expand on the schema. Baseline 3 is appropriate because the schema does the heavy lifting.

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 names a specific verb and resource ('Find a public pay-per-call tool gateway (Monid)') and lists what the tool returns, which makes its core purpose understandable. It does not explicitly contrast itself with siblings like web-fetch or normalize-url, so some differentiation burden falls on the name and niche qualifier, but the purpose is still clear.

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 phrase 'Find a public pay-per-call tool gateway (Monid)' implies the use case: call this when you need Monid gateway setup or remote MCP hop information. However, it offers no explicit when-to-use vs alternatives, no exclusions, and no prerequisites, so the guidance is only implied rather than actionable decision support.

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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