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liara_delete_network

Remove a network from the Liara cloud platform by specifying its network ID to manage infrastructure resources.

Instructions

Delete a network

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
networkIdYesThe network ID to delete

Implementation Reference

  • The handler function that implements the core logic for the 'liara_delete_network' tool. It validates the network ID and sends a DELETE request to the Liara API to delete the network.
     * Delete a network
     */
    export async function deleteNetwork(
        client: LiaraClient,
        networkId: string
    ): Promise<void> {
        validateRequired(networkId, 'Network ID');
        await client.delete(`/v1/networks/${networkId}`);
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Delete a network' implies a destructive mutation, but it doesn't specify whether this action is reversible, requires specific permissions, has side effects (e.g., impacting attached resources), or includes confirmation prompts. This lack of detail is a significant gap for a destructive operation.

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 extremely concise with just three words, front-loading the key action and resource. There is no wasted language or redundancy, making it efficient for quick parsing by an AI agent. This brevity is appropriate given the straightforward tool purpose.

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?

For a destructive tool with no annotations and no output schema, the description is incomplete. It lacks critical context such as behavioral traits (e.g., irreversibility, dependencies), usage prerequisites, and expected outcomes. While the schema covers the parameter, the overall tool understanding remains inadequate for safe and effective use.

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 input schema has 100% description coverage, with the parameter 'networkId' clearly documented as 'The network ID to delete'. The description adds no additional semantic context beyond this, such as format examples or sourcing instructions. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema does the heavy lifting.

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

Purpose3/5

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

The description 'Delete a network' clearly states the verb (delete) and resource (network), which is adequate. However, it doesn't differentiate from sibling deletion tools like liara_delete_app or liara_delete_zone, leaving the agent to infer the specific resource type from the name alone. This makes it vague in distinguishing among similar operations.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., whether the network must be detached first), exclusions, or related tools like liara_detach_network. The agent must rely solely on the tool name and context, which is insufficient for informed usage.

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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