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kubeopsai

k8s-telemetry-mcp

by kubeopsai

get_configuration_history

Retrieve an AWS resource's configuration-change history with field-level diffs, showing what changed and when. Uses AWS Config data to identify related resources for impact analysis.

Instructions

Get the configuration-change history for one AWS resource, with field-level diffs.

Answers "what actually changed on this resource, and when". CloudTrail records that an API call happened; AWS Config records the resulting state, so this is what tells you a security group's ingress rules went from one value to another.

Each change carries a capture time and a config_item_id for citation, plus the resources AWS Config considers related — useful for establishing whether a changed resource is actually connected to a failing one.

Requires AWS Config to be enabled and config:GetResourceConfigHistory.

Args: resource_type: AWS Config resource type, e.g. 'AWS::EC2::SecurityGroup' resource_id: Resource ID, e.g. 'sg-0123456789abcdef0' timeframe_hours: How far back to look (1-720) limit: Maximum configuration snapshots to retrieve (1-100)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
resource_idYes
resource_typeYes
timeframe_hoursNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.2.6

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states that results are field-level diffs, that each change carries capture time, config_item_id, and related resources, and it requires AWS Config to be enabled plus the config:GetResourceConfigHistory permission. This is strong, honest behavioral context for a read-only historical lookup.

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 front-loaded with a precise purpose sentence, then each paragraph earns its place: the CloudTrail contrast explains when to use it, the change-payload details justify citation usefulness, and the prerequisites and Args block are compact. No fluff or redundant restatement.

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?

Despite no annotations and zero schema descriptions, the tool's description alone makes calling it correctly feasible: it covers purpose, prerequisites, permissions, every parameter's semantics, and output characteristics (capture time, config_item_id, related resources). An output schema exists for return structure, so the description is complete enough for an agent to select and invoke the tool appropriately.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It does so thoroughly: each parameter is explained with type, range, and examples—resource_type uses 'AWS::EC2::SecurityGroup', resource_id uses 'sg-0123456789abcdef0', timeframe_hours is '1-720', and limit is '1-100'. This adds substantial meaning beyond the bare schema properties.

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 definition opens with a specific verb+resource: 'Get the configuration-change history for one AWS resource, with field-level diffs.' It distinguishes itself from CloudTrail by explaining that AWS Config records resulting state, not API calls, and it includes concrete examples of resource_type and resource_id.

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 when-to-use context: it answers 'what actually changed on this resource, and when' and contrasts with CloudTrail, which only records that an API call happened. It also states the prerequisite that AWS Config must be enabled and the required IAM permission. However, it does not explicitly compare against the sibling get_resource_history, so the differentiation is not exhaustive.

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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