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JSON Lines row count, body discarded

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

C2.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that only group counts are returned, but it does not disclose network behavior, error handling, timeouts, or whether it performs any side effects. It also does not mention that many parameters are discarded, though that is noted in the schema. The description is too thin to inform an agent about operational risks or limitations.

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 sentence, very concise and front-loaded. There is no wasted wording. However, it is so terse that it omits essential context, but the conciseness itself is appropriate; the issue is under-specification rather than verbosity.

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 9 parameters, no annotations, and no output schema, the description is severely incomplete. It does not explain how to specify the target robots.txt URL, what constitutes a 'group', what the return format is, or how failures are communicated. An agent cannot confidently invoke this tool correctly based on the provided information.

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?

While the schema description coverage is 100%, the parameter descriptions are generic and do not tie to the tool's purpose (e.g., 'url' is described as 'HTTPS URL to normalize or cite' rather than a robots.txt URL). The tool description does not clarify which parameter is the target for fetching robots.txt, leaving an agent to guess. This is a significant gap given the tool has 9 parameters, many of which are unrelated to the described action.

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 states a clear action ('Fetch a public robots.txt') and a specific output ('return group counts only'), which distinguishes its core function. However, it does not differentiate from sibling tools like web-fetch or fetch-status, and the input schema has no parameter that explicitly references robots.txt, so the mapping between the description and the parameters is unclear.

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 such as web-fetch or fetch-status. No context is provided about scenarios where group counts are needed, nor any mention of when not to use it. The description implies a specific use case but leaves the selection entirely to inference.

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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