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Europe/Zagreb clock

fetch-status

HEAD a public URL and return status 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

D1.9/5.0
Behavior1/5

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

With no annotations, the description carries the full burden of disclosing behavior. It only states the basic HEAD request and status return, but omits critical details: side effects, rate limits, handling of the other 8 parameters (which are described as 'discarded' in the schema but not in the tool description), or whether the tool performs network calls for all input types. This is a significant transparency gap.

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, grammatically correct sentence, which is efficient. However, it is overly terse and lacks any structure to convey the multi-parameter nature of the tool. It does not front-load the most important information for all use cases, and the brevity detracts from usefulness.

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 the tool has 9 optional parameters and no annotations or output schema, the description is severely incomplete. It only addresses one of the many apparent capabilities and provides no information about return values, error handling, or prerequisites. An agent cannot reliably determine how to invoke the tool for non-URL inputs.

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 schema provides 100% coverage with per-parameter descriptions, so a baseline of 3 is warranted. However, the tool description adds no parameter guidance and actively misleads by implying only 'url' is relevant, while the schema reveals many other possible inputs. This could cause an agent to ignore the other parameters or misuse them. The description fails to add value beyond the schema and may even confuse.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs an HTTP HEAD request on a public URL and returns only the status. However, the schema lists 9 distinct parameters (city, feed, json, zone, etc.) suggesting the tool supports many other status-check operations beyond URLs. The description covers only the URL case, making the full purpose ambiguous and potentially misleading for non-URL inputs.

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?

No guidance is given on when to use this tool versus its siblings (e.g., web-fetch, normalize-url, browser-url-ok). There is no mention of alternatives, conditions, or exclusions. An agent would have to infer usage from the name and schema alone, which is insufficient.

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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