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KubeCraft MCP Server

Count Custom Resources

count_custom_resources

Count custom resource instances across all CRDs in a Kubernetes cluster. Identify operator bloat by finding abandoned resources and view the top N most numerous CRDs.

Instructions

Cluster-wide CR census: count instances of every CRD. Catches operator bloat — thousands of abandoned CronJobs, sprawling VirtualServices, stale ApplicationSets. Returns top N by count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
groupNoOptional API group filter
top_nNoShow top N CRDs by count (default 50)
min_countNoHide CRDs with fewer than N instances (default 0)
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses it's a cluster-wide scan that returns top N by count, but lacks details on performance, permissions, or whether it filters by namespace. The phrase 'Catches operator bloat' hints at behavioral intent but is not explicit about side effects or requirements.

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?

Three short, focused sentences. First sentence states purpose, second gives usage context with concrete examples, third clarifies output format. No waste; front-loaded with key information.

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

Completeness4/5

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

For a reporting tool with no output schema, the description explains the return is top N by count and gives usage context. It could benefit from specifying the output format (e.g., list of names with counts) but is sufficient for an agent to understand the tool's role.

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 coverage is 100% (all params described). The description adds 'Returns top N by count' reinforcing top_n's role, and mentions bloat detection which aligns with min_count. However, it doesn't provide additional meaning beyond what the schema already states, so baseline 3 is appropriate.

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

Purpose5/5

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

The description clearly states a specific verb+resource: 'count instances of every CRD'. It distinguishes from siblings like list_crds (which lists CRDs without counts) by focusing on counting and returning top N. The phrase 'Cluster-wide CR census' reinforces scope.

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

Usage Guidelines4/5

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

The description gives clear context for when to use: 'Catches operator bloat' with examples (abandoned CronJobs, sprawling VirtualServices, stale ApplicationSets). This implies it's for detecting resource proliferation. No explicit exclusions or alternatives, but the sibling list shows related tools have different purposes.

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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