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Pacific/Majuro clock

hn-front-count

Count current Hacker News front-page stories. Titles 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
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 reveals only that 'Titles discarded' (presumably meaning titles are not returned), but does not disclose whether the tool performs network access, what side effects it has, error behavior, or what the actual return value looks like beyond a count. This is a minimal disclosure for a tool with potential side effects.

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 sentence that front-loads the primary action ('Count current Hacker News front-page stories') and includes a secondary note about titles. It is concise and well-structured, though it could benefit from more detail. It does not waste words, but it is arguably under-specified.

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 9 parameters, no output schema, and no annotations, the description is severely inadequate. It does not explain what the tool returns (a number? a JSON object?), how the parameters affect the count, or why such generic parameters are relevant. An agent cannot confidently call this tool without guessing at the purpose of each parameter. This is far below what is needed for a tool with this complexity.

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 schema descriptions are complete (100% coverage) and each parameter has its own description, so the baseline is 3. The tool description adds no further meaning to the parameters; it does not explain how 'ref', 'city', 'zone', etc. relate to counting HN stories. Since the schema already explains each parameter generically, the description provides no additional value here.

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

Purpose4/5

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

The description clearly states the action: 'Count current Hacker News front-page stories.' This is a specific verb and resource, distinguishing it from sibling tools like web-fetch or fetch-status. However, the mention 'Titles discarded' adds a detail but doesn't fully clarify the tool's exact role among the many 'shape' and 'check' tools, leaving some ambiguity about its scope.

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?

There is no guidance on when to use this tool versus alternatives. The description does not mention any conditions for selection, nor does it contrast with siblings like web-fetch or fetch-status. An agent would have to infer usage from the tool name and description alone, which is insufficient given the large sibling set.

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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