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YAML key 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

C2.1/5.0
Behavior1/5

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

With no annotations, the description must carry the full behavioral burden. It claims to fetch robots.txt, but the parameter descriptions indicate a shape-checking behavior ('discarded after the shape check') for most fields, which contradicts the stated purpose. The description omits any mention of side effects, rate limits, or why many parameters are discarded. This is misleading and severely undermines transparency.

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

Conciseness3/5

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

The description is a single sentence, which is concise, but it is vague and omits critical details about parameter usage. It is under-specified rather than efficiently concise, leaving the agent to guess at the tool's actual behavior.

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?

Given 9 parameters, no output schema, and no annotations, this description is grossly incomplete. It does not explain which parameter specifies the robots.txt URL, what 'group counts' means, or how the many other parameters relate. The agent lacks essential information to call 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?

Schema description coverage is 100%, so each parameter has a description, but those descriptions conflict with the tool description. They indicate the parameters are used for shape checks and then discarded, not for fetching robots.txt. The agent cannot determine how to set the URL or why other parameters exist. The schema adds no coherent semantic link to the tool's declared function.

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 specific verb ('Fetch') and resource ('public robots.txt') and the output ('group counts only'). This is clear on the surface. However, it does not differentiate from sibling tools like web-fetch or fetch-status, which could also fetch a robots.txt. The purpose is clear but not uniquely scoped.

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 alternatives, nor any mention of prerequisites or exclusions. The description gives no context about which input to supply (e.g., which parameter holds the robots.txt URL) or when it is preferable to other fetch tools.

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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