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ay-garg

OpenShift 4 MCP Server

by ay-garg

list_pods

Retrieve a list of pods with namespace, name, status, and node details. Apply filter selectors to target specific pods.

Instructions

List pods with NAMESPACE, NAME, STATUS, READY, RESTARTS, NODE, and AGE columns.

Args: namespace: Namespace to query (empty = all namespaces). label_selector: Label selector (e.g. "app=nginx"). field_selector: Field selector (e.g. "status.phase=Running"). cluster: Named cluster to target (empty = default).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
clusterNo
namespaceNo
field_selectorNo
label_selectorNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It does not mention pagination, result limits, permission requirements, or sorting. The description only lists the output columns. This leaves significant gaps in understanding the tool's behavior.

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 concise, front-loading the core purpose in the first sentence. The parameter block is clean and uses no unnecessary words. Every sentence adds value.

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?

Given the tool outputs an array of objects (as inferred from output schema presence), the description lists key columns, which is helpful. However, it could mention pagination or maximum results for completeness. The need for alternative guidance (e.g., vs run_oc_command) is noted but not critical.

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

Parameters4/5

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

The parameter descriptions (e.g., namespace: 'empty = all namespaces', label_selector: 'e.g. "app=nginx"') add meaningful context beyond the schema, which only has types and defaults. However, the schema coverage is 0%, so these explanations are essential and well done.

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 the tool's purpose: listing pods with specific columns (NAMESPACE, NAME, STATUS, etc.). It distinguishes it from siblings like get_pod (single pod) and other listing tools.

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 explains parameters and default behavior (e.g., empty namespace for all namespaces), but does not explicitly mention when to use this vs alternatives like run_oc_command or get_pod. No when-not guidance is provided.

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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