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Quoted-printable length, input discarded

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

B3.2/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the body is discarded, which is useful, but it does not explain what happens with the many other parameters in the schema (city, feed, json, etc.). The description focuses only on URL, yet the schema suggests a broader purpose, creating ambiguity. There is no mention of rate limits, auth, or error behavior. This is a significant gap.

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

Conciseness5/5

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

The description is a single sentence with no wasted words. It front-loads the core purpose and includes a key behavioral detail (body discarded). It is appropriately concise and easy to parse.

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 9 parameters and no output schema, the description is incomplete. It only addresses the URL use case and does not explain the purpose of the other parameters (city, feed, json, etc.), which are not obviously related to HTTP status checks. An agent cannot understand the full scope of the tool or when it would be appropriate to use it with non-URL inputs. The lack of output schema also means the description should clarify what is returned, but it only vaguely mentions 'status and content type' without detail.

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?

Schema coverage is 100%, so the input schema already documents all 9 parameters. The tool description adds no parameter-specific information beyond what the schema provides. Per the rubric, baseline is 3 for high coverage, and the description does not improve or complement it. It neither clarifies relationships between parameters nor adds usage context.

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

Purpose5/5

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 URL) with a clear scope: 'HTTP status and content type'. It also distinguishes itself from siblings by noting 'Body discarded', which differentiates it from tools like fetch-status that might return more. This is not a tautology and provides clear purpose.

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 provides no guidance on when to use this tool versus alternatives like fetch-status, normalize-url, or browser-url-ok. It does not mention conditions, exclusions, or any selection criteria. The context is implied but no explicit direction is given, leaving the agent to infer usage.

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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