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UTF-8 byte length, text discarded

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

C2.7/5.0
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 only says the JSON values are discarded; it does not disclose whether the call is read-only, whether any parameters trigger network, authorization, or side effects, what happens on malformed JSON, or whether all nine params are treated as alternatives. This leaves core safety and effect questions unanswered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is only two short sentences with zero filler. It front-loads the primary action and then gives a concise behavioral detail about discarded values. Every word earns a place; the brevity is a sign of compression rather than wasted spaces.

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?

Even though the tool appears small in concept, it has 9 optional params, no required params, no output schema, and no annotations, so the description needs to map inputs to behavior. It doesn't say what the tool returns (probably an integer count), which parameter actually holds the JSON object, or what role the other 8 params play leaves the agent unable to confidently construct a correct invocation.

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. Each parameter has a short semantic description in the schema, but the tool description itself adds no extra parameter meaning, and the most important parameter, `json`, is described only as 'JSON text to validate; discarded after the check' — it never says that its keys are counted. This is adequate at the schema level, but the description does not reinforce the intended use.

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 does name a concrete operation ('Count keys in a JSON object') and adds a behavioral note ('Values discarded'), which is well above a tautology. But it never connects that operation to the schema: the only JSON-facing parameter, `json`, is described as 'JSON text to validate; discarded after the check', not as the object whose keys are counted. An agent reading description plus schema cannot confidently tell what single parameter to pass or what the result means.

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?

The description gives no when-to-use signal and does not route the agent toward or away from any sibling such as validate-json or the many shape-check tools. There are no preconditions, no practical examples, and no explicit exclusions, so an agent gains no guidance about choosing this tool versus the alternatives.

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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