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America/Lima 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

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 must carry the full burden. It implies a network fetch and a counts-only output, but does not disclose error behavior, rate limits, or what happens if the robots.txt is missing or unreachable. It also fails to specify which input parameter is actually used for the fetch, despite the schema listing nine parameters.

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 concise sentence, which is good for scannability. However, it omits essential information about parameter usage and behavior, making it under-specified rather than appropriately concise.

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 tool has nine parameters and no output schema, the description is incomplete. It does not explain how to map parameters to the fetch, what constitutes 'group counts', or how errors are handled. An agent would struggle to call this correctly without external knowledge.

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 are generic and not tied to the tool's purpose. For example, 'url' is described as 'HTTPS URL to normalize or cite' rather than as the target for robots.txt. The tool description does not clarify which parameter is relevant or how parameters like 'ref' or 'city' fit into the operation, so the description adds little value over the schema.

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 action ('Fetch a public robots.txt') and output ('return group counts only'), which is clear and distinguishes it from generic fetch tools. However, it does not explicitly differentiate it from sibling tools like 'fetch-status' or 'web-fetch', leaving some ambiguity about when this specific tool is preferred.

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. The description does not mention conditions, prerequisites, or exclusions. An agent would not know whether to pick this over 'fetch-status' or 'domain-shape' without further 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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