Skip to main content
Glama
ranson21

kube-diagnostics-mcp

by ranson21

get_image_inventory

Lists container images, registries, tags, and running digests per Kubernetes workload, flagging unpinned, latest, or moved tags for CVE scanner input.

Instructions

Images, registries, tags, running digests per workload with unpinned/latest/moved-tag findings. Input for a CVE scanner.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namespaceNoKubernetes namespace (required: no default configured; see list_namespaces)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It discloses the scope (per workload, running digests) and the kind of findings (unpinned/latest/moved-tag), which is useful. However, it does not disclose whether this is a read-only operation, whether it aggregates across namespaces, or what the output format looks like. With no annotations, a 3 is appropriate – it adds some behavioral context but not a full picture.

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 sentences with no waste. The first sentence front-loads the core content and scope, and the second sentence states the purpose. The parenthetical about list_namespaces is a useful pointer, though it could be considered slightly tangential.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter tool with 100% schema coverage, the description is reasonably complete. It states the content, scope, and purpose. However, with no output schema and no annotations, it doesn't describe the return format, whether the tool is read-only, or how findings are structured, which an agent might need to interpret the result correctly.

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 schema already documents the namespace parameter. The description adds context that the namespace is a Kubernetes namespace and references list_namespaces for discovery, which is helpful. However, it doesn't explain how the namespace filters the inventory or what happens if omitted, so it adds only marginal value beyond the schema.

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 verb ('get') and resource ('image inventory') and lists concrete content: images, registries, tags, running digests per workload, plus findings about unpinned/latest/moved tags. It clearly distinguishes itself from sibling tools like get_pod_status or get_config, though it doesn't explicitly name a sibling alternative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context: it is 'input for a CVE scanner,' which suggests when an agent needs vulnerability-scanning input. However, it does not state when to use this tool versus alternatives, nor does it mention exclusions or prerequisites beyond the namespace parameter.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.