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agent-tool-index

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

C2.4/5.0
Behavior2/5

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

No annotations are provided, so the description must carry full behavioral transparency. It does mention 'Task text discarded' and some parameter-level notes like 'no disk access', but it fails to disclose whether the tool makes network calls, stores any data, or what side effects the returned 'connection methods' might have.

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 very concise: two short sentences plus one-phrase parameter explanations. There is no fluff or redundant repetition, which makes it easy to scan. The brevity does come at the cost of clarity, but the structure itself is well managed.

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?

With 9 optional parameters and no output schema, the description is not complete enough for an agent to reliably know how to call the tool or interpret the result. It lacks information about return format, error behavior, what happens when no gateway is found, and how parameters should be selected. The sparse parameter notes do not compensate for this missing context.

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?

All 9 parameters have descriptive text, but most descriptions are cryptic and focus on what is discarded rather than how the parameter contributes to the lookup. For example, 'JSON text to validate; discarded after the check' does not explain what validation is performed or how the result affects the returned connection methods. The relationship between parameters and the tool's purpose is unclear.

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

Purpose3/5

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

The description states a clear action ('Find a public pay-per-call tool gateway') and result ('Returns connection methods'), but it does not define what a 'tool gateway' is or what 'connection methods' look like. It also does not distinguish this tool from the many sibling tools that handle similar tasks like weather, search, or validation.

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 example task categories ('weather, search, scrape, or voice') but no concrete guidance on when to use this tool versus alternatives like weather-hint, search-query-len, or validate-json. There is no mention of conditions, exclusions, or preference criteria.

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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