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Read Swarme AI Job Status

swarme_ai_status

Return status and sanitized output for one AI model job.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does convey that the operation returns status and sanitized output, which implies a read-only, non-destructive behavior and discloses that output is sanitized. However, it does not mention error behavior, whether the job runs asynchronously, or what 'sanitized' means in practice.

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 adds meaning, and the key action and object are presented immediately.

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

Completeness3/5

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

The operation is simple with only one parameter and an output schema, but the absence of annotations and usage guidance leaves the agent to infer when to call this instead of related status tools. The description is minimally viable but not fully complete for correct tool selection in a large sibling set.

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

Parameters2/5

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

Schema description coverage is 0%, and the description does not explain job_id beyond the tool name. While job_id is fairly self-explanatory, the description fails to specify where the ID comes from, its expected format, or any constraints beyond the schema's 'required' flag.

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 a specific action ('Return status and sanitized output') on a specific resource ('one AI model job'). It aligns with the tool name and title, and the phrase 'AI model job' distinguishes it from sibling status tools like swarme_tool_status and swarme_experiment_status, though not explicitly.

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 gives no guidance on when to use this tool versus alternatives, how to obtain a job_id, or whether to poll it after swarme_ai_run. With many sibling run/status tools, this lack of usage direction is a clear gap.

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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