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TE / transfer-encoding token shape

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

D1.1/5.0
Behavior1/5

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

No annotations are present, and the description does not clarify side effects, error behavior, or whether all parameters are ignored except one. The parameter descriptions state values are 'discarded' or 'checked' inconsistently, creating confusion about what the tool actually does with the inputs.

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

Conciseness2/5

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

The description is only one sentence and thus highly concise, but it is structurally inadequate because it fails to mention the required 'json' parameter or how to interpret the other 8 parameters. The brevity works against 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 and 9 parameters, the description provides no context about what counts as a key, what the return format is, or how the tool behaves with invalid JSON. The tool is completely underspecified and cannot be used reliably.

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?

Although schema descriptions cover 100% of parameters, they are misleading relative to the tool's stated purpose. For example, 'json' says 'validate' not 'count keys', and other parameters like 'city' or 'zone' have no possible relation to counting keys. The schema adds no meaningful semantics that help an agent use the tool correctly.

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

Purpose1/5

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

The description 'Count keys in a JSON object' is clear in isolation, but the input schema lists 9 unrelated parameters (ref, url, city, feed, host, path, zone, query) with no indication which one contains the JSON object. This makes the actual purpose ambiguous and fails to distinguish it from siblings like validate-json or search-query-len.

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 given on when to use this tool versus alternatives, which parameter to provide, or how to construct a valid call. The description does not mention any required input or selection criteria, leaving the agent with no usable direction.

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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