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get_changes

Read-only

Identify recent Kubernetes changes that may have caused a regression after a deploy or config change. Returns ranked changes with field-level diffs to help pinpoint the cause.

Instructions

Use when the symptom is 'this worked earlier' or 'something broke after a deploy/config change.' Returns recent meaningful changes ranked with spec/config changes first, including field-level diffs for Deployment env/probes and structured ConfigMap data when available. This is often faster than reading ReplicaSet histories or individual audit/log streams, especially when issues are empty or dominated by baseline failures. Pair with since to bound the window; filter by namespace, kind, or name when you know the scope. Omit namespace when the relevant change may be outside the app namespace.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNofilter to a resource kind (e.g. Deployment, Pod)
nameNofilter to a specific resource name
limitNomax changes to return (default 20, max 50)
sinceNoduration to look back, e.g. 1h, 30m, 24h (default 1h)
namespaceNofilter to a specific namespace
Behavior4/5

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

Annotations already declare the tool read-only. The description adds valuable behavioral context: ranking order (spec/config changes first), best-effort field-level diffs ('when available'), and a performance comparison. It does not contradict the annotations.

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 dense, purposeful sentences. The most important usage signal is front-loaded, and every sentence adds either use-case context, behavioral detail, or parameter strategy. No filler.

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?

For a read-only tool with no output schema, the description covers the when, what, why, and how: identifies symptoms, explains return content and ranking, gives performance tradeoffs versus alternatives, and offers filtering strategies. It is fully sufficient for an agent to select and invoke the tool correctly.

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%, so baseline is 3. The description goes beyond the schema by explaining how to use parameters: 'Pair with since to bound the window', 'filter by namespace, kind, or name', and the important tip to 'Omit namespace when the relevant change may be outside the app namespace.'

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 'Returns recent meaningful changes ranked with spec/config changes first, including field-level diffs.' This is a specific verb+resource combination that distinguishes it from siblings like get_events or get_resource, which focus on raw events or static resources.

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?

The description opens with explicit symptoms ('this worked earlier' or 'something broke after a deploy/config change') and names alternatives directly: 'This is often faster than reading ReplicaSet histories or individual audit/log streams.' It also provides concrete parameter guidance, including when to omit namespace.

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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