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Language kn

by io.github.sadri-dridi
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lang-kn

ISO 639 language tag kn.

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
websiteNoPublic https website (homepage domain) to check for agent readiness: robots.txt, llms.txt, sitemap.xml, extractable HTML. Bounded, identified, robots-respecting.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / website
      Added value: +{
+  "description": "Public https website (homepage domain) to check for agent readiness: robots.txt, llms.txt, sitemap.xml, extractable HTML. Bounded, identified, robots-respecting.",
+  "type": "string"
+}
  2. First observed

TDQS

D1.4/5.0
Behavior1/5

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

With no annotations, the description carries the full burden of disclosing side effects, access patterns, and response behavior, but 'ISO 639 language tag kn' discloses none of these. The input schema contains behavioral notes like 'discarded after the shape check' and 'no disk access,' but the description itself adds zero transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short, but this is under-specification rather than appropriate conciseness. A single noun phrase earns its place only if it is meaningful, and here it merely echoes the tool name without explaining purpose or behavior.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 10 optional parameters, no output schema, no annotations, and an ambiguous purpose, yet the description offers no operational context. An agent cannot tell what the many fields represent in combination, what the tool returns, or what side effects to expect.

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%, with all 10 parameters individually described, so the baseline of 3 applies even though the description adds no parameter-level detail. The description's tag phrase does not clarify how the parameters relate, but the schema adequately covers each parameter's basic meaning.

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

Purpose1/5

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

The description is only the noun phrase 'ISO 639 language tag kn,' which essentially restates the tool name without any verb, operation, or resource. It gives an agent no actionable sense of what the tool does or how it differs from siblings such as iana-zones or wiki-title-ok.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description contains no guidance on when to use this tool versus any of the 31 siblings. There are no conditions, exclusions, or alternative tool references, leaving the agent to guess selection 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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