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1sarthakbhardwaj

Labellerr MCP Server

monitor_job_status

Monitor background job progress by submitting the job ID, receiving status updates to know when processing completes or fails.

Instructions

Monitor the status of a background job

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesID of the job to monitor
Behavior2/5

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

With no annotations, the description carries full responsibility for disclosing behavior, but it only states the tool 'monitors' status. It does not explain whether the call blocks until completion, returns immediately with a status snapshot, or requires polling. There is no mention of possible status values, error conditions, or side effects. This lack of detail leaves the agent uncertain about how to interpret the tool's behavior.

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 a single concise sentence that is front-loaded with the verb and object. It avoids unnecessary words and is easy to scan. However, it is slightly under-specified, but that is more a completeness issue than a conciseness problem. The structure is appropriately compact.

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?

Given the absence of annotations and output schema, the description does not provide enough context for an agent to fully understand how to use this tool across the sibling ecosystem. It does not explain how job IDs are obtained, what statuses are returned, or how this differs from other monitor/check tools. The overall context is too vague for reliable correct invocation.

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 already provides 100% coverage for the sole parameter (job_id) with a clear description. The tool description does not add any extra meaning beyond the schema, but the high schema coverage means the parameter is sufficiently documented. Since the schema does the heavy lifting, a baseline of 3 is appropriate.

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 identifies the action (monitor) and resource (job status), so the core purpose is evident. However, it does not distinguish this from sibling tools like monitor_project_progress or monitor_active_operations, which also monitor statuses. The phrase 'background job' is generic and could refer to any asynchronous task.

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?

There is no guidance on when to use this tool versus alternatives such as annotation_check_export_status or monitor_active_operations. No prerequisites, exclusions, or examples of appropriate invocation are provided. The description implies usage for any background job but does not define the context or criteria for choosing this tool.

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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