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America/Montevideo clock

memory-key-count

Count keys in a JSON object. Values 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

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose that values are discarded, but it omits what the count represents (top-level vs nested keys), whether the input must be valid JSON, what is returned, and whether there are side effects. The one disclosed trait is useful but far from sufficient for an unannotated tool.

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 are front-loaded and contain no filler. The description is efficient, but it is so brief that it leaves the parameter mapping and return behavior entirely to the schema, so it does not earn a 5.

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?

With no annotations, no output schema, and nine optional parameters, the description is materially incomplete. It does not state which parameter supplies the JSON object, whether the tool can run with no arguments, or what the caller receives after the count. An agent would have to guess the invocation 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?

Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-level meaning beyond the schema; notably, it never identifies 'json' as the parameter containing the object to count, even though the schema describes it as text to validate. It neither lowers nor raises the baseline.

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 states a concrete action ('Count keys') on a specific resource ('a JSON object') and adds a distinct behavioral note that values are discarded, which separates it from validation-type siblings. It does not differentiate against sibling tools like validate-json or reference the relevant 'json' parameter, but the core purpose is clear.

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 choose this tool over validate-json, domain-shape, or other shape/check siblings, and no exclusions such as 'use X when you need values'. The only implication is that values are not retained, but no explicit alternative is given.

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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