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scale_statefulset

Scale a StatefulSet to a specified number of replicas.

Input Schema

NameRequiredDescriptionDefault
dry_runNoIf true, preview the change without executing it.
replicasYesTarget number of replicas (0-100).
namespaceYesKubernetes namespace where the StatefulSet is located.
cluster_idYesAnkra cluster id (UUID) the call targets. Discover ids with list_clusters.
statefulset_nameYesName of the StatefulSet to scale.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=false, idempotentHint=false and destructiveHint=false, and the description adds nothing on top: it does not say what happens at replicas=0 (workload effectively down), whether the operation waits for pods to converge, or what auth/permission is required. For a mutation tool the description contributes no behavioral context of its own.

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

Conciseness4/5

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

A single compact sentence with the action front-loaded and no filler. It is efficient, though the brevity tips into under-specification rather than optimal density.

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

Completeness2/5

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

No output schema exists, so the description should carry the return and side-effect story, but it omits dry_run usage, scale-to-zero implications, failure behavior and sibling routing. For a 5-parameter mutation tool, this leaves an agent with too little to invoke it confidently.

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

Parameters3/5

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

Schema description coverage is 100%, so namespace, statefulset_name, replicas (with 0-100 bounds), cluster_id and the dry_run preview flag are all documented in the schema itself. The description only echoes the replicas argument and adds no format, range or dry-run semantics beyond it, so the baseline 3 applies.

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

Purpose4/5

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

The description gives a specific verb (scale) and resource (StatefulSet) plus the target (a specified number of replicas), so the action is unambiguous. However, it never distinguishes itself from the near-identical sibling scale_deployment, which an agent choosing between the two would need.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no mention of prerequisites (e.g. that the StatefulSet must already exist), and no pointer to alternatives such as scale_deployment or get_statefulsets for discovering the target. The sentence describes only the mechanical action.

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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