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Pacific/Guadalcanal clock

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. First observed

TDQS

B3.1/5.0
Behavior3/5

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

There are no annotations, so the description carries the burden of behavioral disclosure. It does reveal that the tool fetches a public resource and returns only group counts, not the full robots.txt. But it does not explain error behavior, redirects, timeouts, or what happens when robots.txt is missing, which are relevant for a network-fetching tool.

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. Words like 'public' and 'only' add useful scope. It is appropriately concise, though the conciseness comes at the cost of omitting parameter semantics.

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?

Given the confusing multi-parameter schema, the absence of annotations, and no output schema, the description is too sparse. It does not explain which parameter supplies the robots.txt URL, what 'group counts' means structurally, or what the return value contains. An agent would likely need to open the schema and still be unsure how to invoke 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?

The input schema contains eight parameters with high schema coverage, but the descriptions are disconnected from the tool's stated purpose: url is 'HTTPS URL to normalize or cite', host is 'Public hostname', and none of the parameters is described as the robots.txt URL. The tool description adds no parameter mapping, so an agent cannot confidently determine which argument identifies the target robots.txt.

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 a specific verb and resource: 'Fetch a public robots.txt' and narrows the output to 'group counts only.' It is easy to understand what the tool does, though it does not explicitly differentiate itself from sibling tools like web-fetch or fetch-status.

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

Usage Guidelines3/5

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

The phrase 'Fetch a public robots.txt and return group counts only' implies when to use it: when an agent needs only robots.txt group counts rather than the full file. However, it does not explicitly state when not to use it or mention alternative tools such as web-fetch or normalize-url, leaving the when-to-use guidance implicit.

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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