get_scaling_history

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

No annotations are provided, so the description carries the full burden. It discloses an important dependency on kube-state-metrics for historical data and constrains the timeframe range, which adds behavioral context. However, it does not mention read-only behavior, potential failure modes, or what 'current autoscaler status' includes beyond the basic operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded: the purpose is stated in the first sentence, followed by a critical prerequisite and a clean Args block. Every sentence adds value without redundant wording.

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

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

For a tool with three simple optional parameters and an output schema, the description covers the essential inputs and the main dependency. It lacks explicit guidance on when to use it among the sibling tools, but the purpose and parameter semantics are sufficiently complete for correct invocation.

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

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

Schema description coverage is 0%, but the description compensates by explaining all three parameters: namespace, optional deployment filter, and timeframe in minutes with a valid range. This gives the agent enough semantic understanding to call the tool with correct arguments, though each explanation is brief.

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

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

The description clearly states the tool retrieves HPA scaling history and current autoscaler status for deployments, using a specific verb and resource. It does not explicitly distinguish itself from sibling tools, but the focus on HPA scaling is specific enough to differentiate it from nearby tools like get_pod_metrics or get_recent_deployments.

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

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

The description includes a useful prerequisite ('Requires kube-state-metrics for historical data'), which helps the agent understand a condition for successful use. However, it does not state when to prefer this tool over alternatives such as query_prometheus or get_pod_metrics, so usage guidance is mostly implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.