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Facets-cloud

Facets Module MCP Server

by Facets-cloud

check_deployment_status

Check the status of a deployment using cluster ID and release trace ID. Optionally wait for completion with adjustable timeout and polling interval.

Instructions

Check the status of a deployment.

Args: cluster_id (str): The ID of the environment where the deployment is running release_trace_id (str): The release trace ID of the deployment to check wait (bool): If True, wait for the deployment to complete (either succeed or fail) timeout_seconds (int): Maximum time to wait for completion in seconds (default: 300s / 5min) poll_interval_seconds (int): Time between status checks in seconds (default: 5s)

Returns: str: JSON with deployment status information

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cluster_idYes
release_trace_idYes
waitNo
timeout_secondsNo
poll_interval_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description explains the wait mechanism, timeout, and poll interval. However, it does not disclose if the tool is read-only or has side effects, nor does it mention authentication or rate limits.

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 well-structured with a clear header, parameter list, and return statement. It is concise yet comprehensive, with no redundant information.

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?

For a status-check tool, the description covers inputs, behavior, and output format. It lacks error handling details and explicit safety info, but given the output schema exists, it is reasonably complete.

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

Parameters4/5

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

Schema coverage is 0%, so the description must compensate. It explains all five parameters with their roles, defaults, and semantics (e.g., wait, timeout, poll). This adds significant value beyond the schema.

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 clearly states the tool checks deployment status. It lists parameters but does not distinguish it from the sibling 'get_deployment_logs', which could also relate to monitoring.

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?

No guidance on when to use this tool versus alternatives like get_deployment_logs. No explicit when-to-use or when-not-to-use context.

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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