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Recipe change status

get_recipe_change
Read-onlyIdempotent

Retrieve a recipe change job by jobId to check its status, pull request, branch, or failure reason after proposing a change.

Instructions

Return one recipe change job by jobId (the jobId propose_recipe_change returned): { id, element, status, pr_url, pr_number, branch, error, batch_id, created_at, started_at, finished_at }. status moves queued → running → pr_opened, or ends rejected or failed with the reason in error; a job stuck past its deadline reads as failed. Optional projectId. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdYesThe jobId propose_recipe_change returned
projectIdNoProject UUID — defaults to the server-configured project when omitted (`project_id` is accepted too.)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.14

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/idempotentHint/openWorldHint, so the safety profile is covered. The description adds real behavioral context beyond them: the status state machine (queued → running → pr_opened, rejected, failed), that error carries the failure reason, and that a job past its deadline reads as failed.

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?

Purpose is front-loaded in the first clause, followed by the return-field list and lifecycle semantics. Slightly dense with the inline field enumeration, but every element earns its place given there is no output schema.

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 enumerating the returned fields and explaining the terminal statuses and deadline failure behavior. Combined with the jobId/projectId guidance, an agent has everything needed to call and interpret the result.

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 description coverage is 100%, so both parameters are already documented in the schema, including the projectId default. The description only notes 'Optional projectId' and the jobId source, adding no syntax or format detail beyond what the schema provides — the baseline 3 is appropriate.

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 a specific verb and resource ('Return one recipe change job by jobId') and names propose_recipe_change as the originating tool, which lets an agent distinguish it from other get_* siblings without opening a schema.

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 makes the usage context clear by tying jobId to the value propose_recipe_change returned, implying this is the follow-up status-polling call. It does not state explicit when-not conditions, but there is no competing sibling that would be confused with it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.