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get_dashboard

Read-only

Retrieve a cluster or namespace health dashboard with resource counts, failing pods, and warning events to rank likely problems before deep-diving.

Instructions

Use for inventory-style cluster or namespace health triage, like kubectl get all plus detected problems and warning events in one call. Returns resource counts, failing pods, unhealthy workloads, recent Warning events, and Helm release status so you can rank likely suspects before calling get_resource or logs. Routing: unknown broken thing -> issues; content/name search -> search; service routing/dependencies -> get_topology or get_neighborhood; inventory/counts/Helm/events overview -> get_dashboard. Use namespace for app-local triage; omit it when the root may be cluster-scoped.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namespaceNofilter to a specific namespace. Use when triaging one app/tenant namespace before drilling into individual resources.
Behavior4/5

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

Annotations already provide readOnlyHint=true, so the safety profile is known. The description adds behavioral context by explaining that it returns an overview for ranking suspects before drilling into get_resource or logs, and describes the scope (cluster vs namespace). It does not mention any limitations like permission requirements or performance, but given the annotation coverage, this is sufficient.

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 dense with useful information but not bloated. Every sentence adds value: purpose, return content, routing, and namespace guidance. The structure with a routing list is efficient and easy to scan.

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

Completeness5/5

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

Given no output schema, the description compensates by enumerating what the tool returns. It covers when to use, how to decide among siblings, and parameter semantics. For a single-optional-parameter tool, this is complete.

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?

Schema coverage is 100% and the schema description already explains the namespace filter. The description adds usage nuance: 'Use namespace for app-local triage; omit it when the root may be cluster-scoped.' This goes beyond the schema and clarifies when to set vs omit the parameter.

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 defines the tool's purpose: inventory-style cluster/namespace health triage, analogous to `kubectl get all` plus problem detection. It specifies the exact returned content (resource counts, failing pods, unhealthy workloads, Warning events, Helm status) and distinguishes it from siblings by naming what it is NOT for.

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

Usage Guidelines5/5

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

Provides explicit routing rules: 'unknown broken thing -> issues; content/name search -> search; service routing/dependencies -> get_topology or get_neighborhood; inventory/counts/Helm/events overview -> get_dashboard.' Also gives namespace usage guidance (use for app-local, omit for cluster-scoped), which is exceptionally clear.

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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