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lib-docs-hint

HTTP status for a public library docs 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

D1.7/5.0
Behavior2/5

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

The description mentions 'Body discarded,' which is a behavioral trait. However, annotations are absent, so the description carries the full burden. It does not disclose that the tool handles multiple input types (as implied by parameters like city, zone, query) or what happens for each type. The description is misleading because it focuses solely on HTTP status while the schema indicates broader functionality.

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 extremely short and front-loaded, which is good for conciseness. However, it is under-specified and lacks necessary detail, making it too sparse to be useful. It earns a middle score because it is not verbose, but it sacrifices clarity for brevity.

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?

For a tool with 9 parameters, no output schema, and no annotations, this description is critically incomplete. It explains only one use case and does not address the other parameters, return values, or error scenarios. An agent would have no idea how to use the other parameters or what results to expect.

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

Parameters1/5

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

The schema has 100% coverage, so the baseline is 3, but the description fails to connect the parameters to the tool's purpose. It describes only URL-related behavior, yet the parameters include unrelated fields (ref, city, feed, json, path, zone, query). The description contradicts the parameter list and provides no additional meaning; it actually confuses parameter usage.

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

Purpose2/5

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

The description states it returns HTTP status for a public library docs URL, which is a specific action and resource. However, the parameter schema includes unrelated fields like city, zone, query, and json, suggesting the tool actually performs multiple types of checks. The description does not align with the parameter list and does not differentiate it from sibling tools like fetch-status or web-fetch, leaving the true purpose ambiguous.

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 provided on when to use this tool versus alternatives such as fetch-status, web-fetch, or normalize-url. It does not mention conditions, exclusions, or prerequisites. The description is a single sentence with no usage context.

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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