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EAN/UPC digit 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

C2.7/5.0
Behavior2/5

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

With no annotations provided, the description must disclose behavioral traits. It implies a network fetch and a reduced output, but does not mention error handling, authentication, rate limits, or what happens with invalid inputs. It also fails to explain how the listed parameters (url, host, json, zone) relate to the action, leaving behavior opaque.

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

Conciseness5/5

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

The description is a single, compact sentence with no filler or redundancy. It conveys the core action and output in an efficient, front-loaded manner.

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 four parameters (all optional) and no output schema or annotations, yet the description gives no indication of expected inputs, required fields, return format, or error behavior. The parameter mismatch compounds the incompleteness, leaving an agent without enough information to use the tool correctly.

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?

Although schema coverage is 100%, the parameter descriptions (e.g., 'HTTPS URL to normalize or cite', 'JSON text to validate') do not align with the stated action of fetching robots.txt. The description adds no clarification on how these parameters are used, and the mismatch suggests either a misleading description or an erroneous schema, making parameter semantics poor.

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 clearly states the action ('Fetch a public robots.txt') and the output ('return group counts only'), making the purpose specific and distinguishable from generic tools. However, it does not differentiate from siblings like citation or normalize-url, and the parameter schema appears unrelated to the stated purpose, which slightly undermines clarity.

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 provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, contexts, or conditions where this tool is preferred, nor does it name any sibling tools or exclusions.

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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