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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

C2.8/5.0
Behavior3/5

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

No annotations are provided, so the description bears the full burden. It does disclose the core fetch behavior — returns HTTP status and content type, discards the body — which is genuinely useful. But it hides that the tool accepts 8 other input types (ref, city, zone, json, path, query, feed, host), each described in the schema as checked and discarded, revealing a far broader shape-validation role than the description implies.

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?

Two short sentences with no filler, front-loaded around the primary outcome. Textually efficient, though the brevity purchases clarity for the URL case at the expense of five-sixths of the parameters.

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?

For a tool with 9 parameters, no annotations, and no output schema, a single line about URL status is grossly insufficient. It omits the behavior for the eight non-URL parameters, return format beyond 'status and content type,' and error semantics. An agent cannot infer how to exercise the city, zone, json, or path inputs from this description.

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 description coverage is 100%, so the baseline is 3. The description adds mild value by clarifying expected output for a URL input (status and content type, body discarded), but it never explains how the other eight parameters relate to the tool or what they return. The schema descriptions carry the real semantic weight.

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 specific output verb+resource — HTTP status and content type for a public URL, body discarded — which is clear on its face. However, it describes only one of nine schema parameters; the schema covers git refs, cities, timezones, JSON, file paths, and query text, implying the tool actually validates many input shapes. It also doesn't distinguish itself from overlapping URL siblings like fetch-status or browser-url-ok.

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?

No guidance on when to use this tool versus alternatives. Overlapping siblings (fetch-status, browser-url-ok, playwright-url-ok) are never referenced. The only implicit signal is 'Body discarded,' hinting it suits status/content-type checks rather than content extraction, but this is left entirely to 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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