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Get Job Status

get_job_status
Read-onlyIdempotent

Check the status of a job (a create, deploy, promotion, rollback or deletion). STATUS VALUES: pending (queued), processing (in progress), completed (success), failed. Call it until the status is completed or failed: every job ends, since a job whose server stopped is failed within about three minutes, and a deploy can take up to 15 minutes. If status is 'failed', read failure_side and error: 'customer' means the project's input is proven the cause (an invalid schema, data the new schema does not fit, a change the resource pool cannot hold), and error says what to change; 'platform' means no input of the project is known to cause it: report it to RationalBloks rather than changing the schema.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesJob ID returned from deployment operations

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already mark the tool read-only and idempotent, and the description adds rich, non-obvious behavior: terminal states, guaranteed eventual completion, timeout estimates, and failure-side semantics. This significantly exceeds what the annotations and schema convey.

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?

Although longer than typical descriptions, every sentence is information-dense and earns its place. The description is front-loaded with the core purpose, then flows naturally through status values, polling guidance, and failure handling without repetition or filler.

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

Completeness5/5

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

With no output schema, the description compensates by explaining the status vocabularyable, terminal behavior, and relevant output fields (failure_side, error). The implementation guidance is sufficiently complete for an agent to poll and react correctly across all branches.

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 single parameter job_id has full schema description coverage ('Job ID returned from deployment operations'), so the schema carries the semantic weight. The tool description adds no further parameter-specific meaning, which is acceptable given 100% coverage.

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?

States the specific verb 'Check' and resource 'status of a job', and enumerates the job operations it applies to (create, deploy, promotion, rollback, deletion). This is unambiguous and distinct from the deployment-creation siblings, so an agent knows exactly what this tool observes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit polling instructions: call until 'completed' or 'failed', with concrete time expectations for failed servers and deploy duration. It also tells the agent what to do on 'failed' based on failure_side, including the key exclusion that 'platform' failures should be reported rather than fixed via schema changes.

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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