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ISO country ML

search-query-len

Count characters in a search query. Query 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

C2.6/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It does say 'Query discarded', which is useful, but it never explains what is returned, how characters are counted, or what happens when the other schema parameters are supplied. For a tool with a large and seemingly unrelated schema, this is insufficient.

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 only two short sentences and front-loads the core action. It contains no filler, though the extreme brevity is a tradeoff against completeness.

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?

This tool has nine parameters, no output schema, and no annotations, but the description only acknowledges the query parameter and gives no return semantics. The schema helps with parameter meanings, but the overall definition is not complete enough for an agent to confidently invoke the tool.

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%, and each parameter has a written purpose in the schema. The description adds little beyond what is already stated for the query parameter, so the schema is doing the heavy lifting and a baseline of 3 is appropriate.

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 specific operation ('Count characters in a search query') and notes that the query is discarded, which gives the agent a basic idea of purpose. However, the input schema exposes nine unrelated parameters (ref, url, city, feed, json, path, zone), and the description does not explain how they relate to the stated purpose, leaving real ambiguity.

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?

There is no guidance about when to use this tool versus siblings like validate-json, normalize-url, or file-path-ok. The phrase 'search query' weakly implies a use case, but no conditions, exclusions, or alternatives are mentioned.

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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