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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

D1.9/5.0
Behavior2/5

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

No annotations are present, so the description carries the full burden of explaining behavior. It mentions that values are discarded but does not state whether the operation is read-only, whether any input is required, what errors may occur, or how malformed JSON is handled.

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 itself is concise and front-loaded with the main action. However, it is too terse to resolve the ambiguity created by the mismatched input schema, so the brevity comes at the cost of necessary clarity.

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?

With no output schema, no examples, no error semantics, and an input schema that seems copied from unrelated tools, the description is not complete enough for an agent to confidently select and correctly invoke this tool. The missing parameter mapping is a critical gap.

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 nine parameters, but their descriptions are largely unrelated to counting keys in a JSON object. For example, the 'json' parameter is described as 'JSON text to validate; discarded after the check' rather than as the object whose keys should be counted, and other parameters like 'url', 'city', 'zone', and 'query' have no evident connection to the tool's purpose.

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 clearly states the core operation: 'Count keys in a JSON object. Values discarded.' However, the input schema exposes nine unrelated optional string parameters, and none of their descriptions clearly identify which parameter is the JSON object whose keys should be counted, creating ambiguity about how to invoke the tool.

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?

There is no guidance about when to use this tool versus any of the many sibling tools. No conditions, prerequisites, or examples are provided, so an agent cannot determine when this tool is the appropriate choice.

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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