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Glama

scale_replicas_down

Destructive

Lower a production deployment's replica count to reduce inference capacity; the action is reversible, and dry_run previews changes to avoid stranding in-flight requests.

Instructions

[WRITE][risk=high] Lower a deployment's replica count on prod (reversible → prior).

Fewer replicas can strand in-flight requests — pass dry_run=True to preview.

Args: application: Serve application name. deployment: Deployment name. num_replicas: New (lower) replica count. dry_run: If True, preview without scaling. target: Inference target name from config; omit for the default.

Input Schema

NameRequiredDescriptionDefault
targetNo
dry_runNo
deploymentYes
applicationYes
num_replicasYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare the operation as non-read-only and destructive. The description adds meaningful context beyond that: high risk level, reversibility to the prior count, and the side effect of potentially stranding in-flight requests, with dry-run as a mitigation.

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?

The description is front-loaded with a compact risk/direction prefix and then structured arguments. The fit is appropriate for a five-parameter tool with no schema descriptions, though the phrase 'reversible → prior' is slightly cryptic and could be clearer.

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

Completeness4/5

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

Given the complexity (write, high-risk, destructive, five parameters, no output schema), the description covers the critical behavioral and parameter details. It could mention permissions or the interaction with undo/rollback tools, but is otherwise complete enough for correct invocation.

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 carries the full burden of explaining parameters. It documents all five parameters, including optional ones, with clear semantics: application name, deployment name, new lower replica count, dry_run preview behavior, and target defaulting.

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?

States a specific verb ('Lower') and resource ('deployment's replica count') with production scope. The directionality directly distinguishes it from the sibling scale_replicas_up, so an agent can select it without opening the schema.

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

Usage Guidelines3/5

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

Provides a useful operational hint ('pass dry_run=True to preview') and notes the risk of stranding in-flight requests. However, it never states when to choose this tool over alternatives like scale_to_zero or autoscale_config_update, leaving the core when-to-use decision implied by the name.

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