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Glama

ISO country NZ

web-fetch

HTTP status and content type for a public URL. Body discarded.

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?

With no annotations present, the description must carry the behavioral disclosure burden. It does add one useful trait – 'Body discarded' – and scopes input to 'public URL.' But it completely omits the fact that non-URL parameters (ref, city, json, feed, host, path) are accepted and discarded, so the agent is unaware of these behaviors and may be misled about what the tool can handle.

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 wasted words: it states the expected output and the body-discard behavior upfront. The brevity is structurally good, though it contributes to the overall incompleteness.

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 a 7-parameter schema, no output schema, and no annotations, a one-sentence description is clearly insufficient. The agent is left without details on return shape, error cases, which parameter to use when, or the purpose of the many non-URL inputs. The current description only covers a narrow slice of the tool's actual contract.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides descriptions for every parameter (100% coverage), including notes like 'discarded after the shape check,' so the baseline is 3. The description adds no extra parameter-level meaning; it only reinforces the URL path, and could even mislead an agent into ignoring the other parameters.

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 states a concrete result – 'HTTP status and content type for a public URL' – and adds the behavior 'Body discarded.' However, it captures only one of the many input types visible in the schema (ref, city, json, etc.), so the purpose statement is incomplete and not a true representation of the tool's full scope. It also fails to differentiate from siblings like fetch-status or normalize-url, since nothing indicates what makes this tool's status/content-type result distinct.

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?

The description gives no guidance on when to use this tool versus any of its many siblings, such as fetch-status, browser-url-ok, or normalize-url. There is no mention of conditions, exclusions, or alternatives, leaving the agent to infer the appropriate context on its own.

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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