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Get spec or job status

get_status
Read-onlyIdempotent

Poll the current status of a data spec analysis or data-load job by providing either its specId or jobId.

Instructions

Poll the status of either a data spec's analysis (pass specId, reaches "ready"/"failed") or a data-load job (pass jobId, reaches "complete"/"failed"). Pass exactly one of specId or jobId.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdNoPoll a data-load job's status. Pass exactly one of specId or jobId.
specIdNoPoll a data spec's analysis status. Pass exactly one of specId or jobId.
workspaceIdNoWorkspace to act on. Defaults to your only workspace if you have exactly one.
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds value by specifying the terminal states for each resource type and the constraint 'exactly one of specId or jobId', which enriches understanding of behavior beyond the annotations.

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—two sentences—and front-loads the purpose and key constraints. Every word contributes, with no redundancy or filler.

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?

The tool is a simple status poll with three parameters and no output schema. The description covers both use cases, the required parameter selection, and expected terminal states. It does not describe the return format, but for a status tool this may be assumed; overall, it is sufficiently complete for an agent to use correctly.

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?

Schema coverage is 100% with each parameter (jobId, specId, workspaceId) described directly. The description essentially echoes the mutual exclusivity already present in the schema and adds terminal states, but these are behavioral details rather than parameter semantics. Thus, it does not substantially enhance parameter understanding beyond the schema.

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

Purpose5/5

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

The description clearly states it polls status for two distinct resources (data spec analysis or data-load job) with specific terminal states ('ready'/'failed' and 'complete'/'failed'), and explicitly distinguishes the parameter use. It is specific and differentiates from sibling tools that perform actions like run/finish data jobs.

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?

The description provides clear context: when to poll status (during analysis or job execution) and the required mutual exclusivity of specId/jobId. It does not explicitly mention alternative tools, but the action 'poll' makes its role obvious among siblings like run_data_job or finish_data_job.

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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