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ISO 4217 currency shape

inspect-robots

Fetch a public robots.txt and return group counts only.

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. Changed5 schema fields changed
    • addedInput schema / properties / city
      Added value: +{
      +  "description": "City name for a public weather hint; discarded after the call",
      +  "type": "string"
      +}
    • addedInput schema / properties / feed
      Added value: +{
      +  "description": "Public RSS or Atom URL; titles discarded",
      +  "type": "string"
      +}
    • addedInput schema / properties / path
      Added value: +{
      +  "description": "File path to check; no disk access",
      +  "type": "string"
      +}
    • addedInput schema / properties / query
      Added value: +{
      +  "description": "Search text; discarded after the length check",
      +  "type": "string"
      +}
    • addedInput schema / properties / ref
      Added value: +{
      +  "description": "Git ref name; discarded after the shape check",
      +  "type": "string"
      +}
  2. First observed

TDQS

C2.3/5.0
Behavior1/5

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

With no annotations, the description carries the full burden, but it fails to disclose critical behavior and actively conflicts with the input schema. The schema parameters ('normalize or cite', 'JSON validate', 'IANA timezone') have nothing to do with fetching robots.txt, so an agent cannot infer how the tool actually behaves.

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 a single, front-loaded sentence with no filler. It is concise and readable, though the conciseness comes at the cost of missing essential information.

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 definition is severely incomplete for a tool with 4 parameters, no annotations, and no output schema. It does not explain how to specify the robots.txt URL, what 'group counts' means, or why the schema contains unrelated parameters, leaving an agent unable to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although schema coverage is 100%, all four parameter descriptions are generic and unrelated to the tool's stated purpose. The 'url' parameter is described as 'HTTPS URL to normalize or cite' rather than the site whose robots.txt should be fetched, and 'json' and 'zone' have no connection to robots.txt at all. This makes the parameters misleading rather than meaningful.

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 uses a specific verb ('Fetch') and resource ('public robots.txt') and states the result ('return group counts only'). This makes the intended action clear in isolation, though it doesn't explicitly differentiate from sibling tools.

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 on when to use this tool versus alternatives, no prerequisites, and no exclusions. The only hint is 'return group counts only,' which is a scoping constraint rather than usage direction.

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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