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EAN/UPC digit shape

compatibility

Show how this request is classified. No identifiers are retained.

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

D1.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. The only behavioral statement is 'No identifiers are retained,' which addresses privacy but not what the tool does with inputs, whether it is read-only, or what side effects occur. The core behavior (classification) is entirely unexplained.

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 a single short sentence, which is under-specified rather than concise. It omits critical information that the agent needs, so the brevity is not a strength. The privacy note is front-loaded but not the actual purpose.

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?

With four parameters, no output schema, and no annotations, the description is severely incomplete. An agent cannot determine what the tool does, what it returns, or how to use it correctly. The description fails to explain the classification concept or the role of each parameter, making the tool nearly unusable without external knowledge.

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 schema covers 100% of the four parameters, each with a description, so the baseline is 3. The description adds nothing about how these parameters relate to the classification or how they should be combined. It does not compensate for any gaps because there are none in the schema, but it also does not add value beyond the schema.

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

Purpose2/5

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

The description 'Show how this request is classified' is vague. It does not specify what 'request' means, what kind of classification is performed, or what the output looks like. It also does not differentiate from sibling tools like normalize-url or validate-json, which handle specific inputs. The name 'compatibility' hints at a purpose, but the description itself is not clear.

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?

There is no guidance on when to use this tool versus its siblings. The description provides no context about scenarios, prerequisites, or alternatives. An agent would have no idea whether to pick this over cite, inspect-robots, or validate-json.

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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