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Scale service

service_scale
Idempotent

Scale Lizard services by adjusting replica count, CPU, memory, or storage limits to handle changing workload demands.

Instructions

Use this when the user wants to change replica count, CPU, memory, or storage limits for a Lizard service.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cpuNoCPU cores, apps only
memoryNoMemory in MB, apps only
projectYes
serviceYes
storageNoStorage in MB, addons only, grow-only
replicasNoApps only
Behavior3/5

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

The annotations already convey mutation (readOnlyHint=false), idempotency (idempotentHint=true), and non-destructiveness (destructiveHint=false). The description adds no behavioral details beyond the verb, such as whether scaling causes restarts. This is acceptable but not rich; no contradictions exist.

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 a single, front-loaded sentence with no filler. Every word supports tool selection and invocation.

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?

Together with the input schema, which documents units, allowed values, 'apps only'/'addons only' constraints, and grow-only storage, the description gives enough context for an agent to select and call the tool correctly. It could add operational side-effects like downtime or restart behavior, but those are not essential for the basic call.

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?

The description names the main scaling dimensions (replicas, CPU, memory, storage), which maps well to the schema properties. However, it does not add details beyond what the schema descriptions already provide, and the required project/service parameters remain undocumented in the description. At 67% schema coverage, this is adequate but not exceptional.

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 names a specific action ('change') and the resources involved ('replica count, CPU, memory, or storage limits') for a Lizard service, making the tool's purpose clear. It does not explicitly contrast with sibling tools like service_set, but the field list and 'scale' title are enough to separate it from most alternatives.

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?

It opens with explicit 'Use this when the user wants to change...', giving a clear trigger condition. It does not name alternatives or say when not to use this tool, but the phrasing provides adequate usage context for common scale requests.

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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