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aywengo

MCP Kafka Schema Reg

count_contexts

Count contexts in a Kafka Schema Registry to monitor registry size and organization. Get a total for inventory or validation.

Instructions

Count the number of contexts in a registry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
registryNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changedv2.2.2
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / properties / registry / title
      Removed value: -"Registry"
  2. First observedv1.0.0

TDQS

C2.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the transparency burden. 'Count' implies a non-mutating read operation, which is useful, but the description does not disclose what happens when the nullable registry parameter is null, what errors may occur, or what result shape to expect.

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 terse sentence with no filler, and the core action is front-loaded. It is efficient, though it could add a clarifying note about the default registry without becoming bloated.

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 a nullable defaulted parameter, the description leaves key information unresolved: what omitting registry means, whether a registry is required at all, and what the returned count looks like. The tool is simple, but the definition is not complete enough for confident autonomous invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for the undocumented parameter. It only restates the role of 'registry' without explaining the null/default behavior or acceptable values, leaving an important ambiguity for the only parameter.

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 specific action ('count'), a resource ('contexts'), and a scope ('in a registry'), so it is clear what the tool does. It is distinguishable from siblings like list_contexts and count_schemas, though it does not explicitly name or contrast them.

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 about when to use this tool versus alternatives such as list_contexts, count_schemas, or get_registry_info. The description gives no context for when a registry should be supplied or omitted, leaving usage entirely to inference.

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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