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Get background job status

get_job_status
Read-onlyIdempotent

Check if a background OpenProject job (project copy, deletion, export) has finished, and get its status, success flag, and result URL.

Instructions

Check whether a background job (a project copy, a scheduled deletion) has finished.

OpenProject runs copies, deletions and exports asynchronously and hands back a job id. This is the only way to learn what happened to one: call it after copy_project or delete_project and wait for a terminal state before reporting an outcome to the user.

Returns {id, status, finished, successful, message, project, result_url, notes}. status is 'in_queue' or 'in_process' while the job runs and 'success', 'failure', 'error' or 'cancelled' once it is over; finished and successful are derived from it, and successful stays null while the job runs rather than defaulting to false. A finished copy reports the new project in project and the URL it lives at in result_url.

Pitfalls: a 200 does not mean the job worked — read status. Polling is on you: wait a few seconds between calls rather than looping tightly. OpenProject drops job statuses after a while, so a 404 can mean 'long finished' as easily as 'wrong id'; confirm with get_project or list_projects. When a job fails, message is what OpenProject recorded — there is no API to retry it, so the underlying tool has to be called again deliberately.

Cross-references: copy_project and delete_project produce the job_id; get_project / list_projects verify what the job actually did.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesBackground job id — a uuid such as '9f4c1d5e-0e2a-4f2b-9a11-2f1b3c4d5e6f'. It comes from copy_project or delete_project ('job_id' in their results), never from a project id.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoJob id (a uuid) this status belongs to.
notesNoDegradation markers: still running, or a reference that had to be derived.
statusNoJob state: 'in_queue' or 'in_process' while it runs, 'success', 'failure', 'error' or 'cancelled' once it is over.
messageNoWhat the job reported, e.g. why it failed.
projectNoProject the job produced or acted on ({id, name}), when it names one — this is how a finished copy_project job hands back the new project.
finishedYesTrue once status is terminal. False means the job is still running — poll again rather than reporting a result.
result_urlNoWeb URL the job stored for its result (the new project, an export download). A UI URL, not an API endpoint.
successfulNoTrue when the job finished successfully, false when it failed, null while it is still running. Never guess from 'finished' alone.
Behavior5/5

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

Beyond the annotations (readOnly, idempotent, etc.), the description adds rich behavioral detail: status value lifecycle, derived fields, the meaning of a 200 response, polling requirements, job status expiration, 404 interpretation, failure message behavior, and lack of retry API. This goes far beyond what annotations alone 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?

The description is long but every sentence earns its place: purpose, background, return format, pitfalls, and cross-references are clearly segmented. It is front-loaded with the core purpose and structured for quick scanning despite its length.

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?

For a single-parameter polling tool, the description is exceptionally complete: it covers return fields, all possible statuses, edge cases (404, successful null), polling best practices, and verification alternatives. The presence of an output schema means return details need not be fully restated, but the description still provides them, ensuring no gaps.

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's description for job_id already covers its provenance (uuid from copy_project/delete_project) and distinction from project id. The tool description reinforces this but adds no new parameter-specific semantics beyond usage context, so the baseline 3 for high schema coverage (100%) applies.

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 opens with a specific verb and resource: 'Check whether a background job (a project copy, a scheduled deletion) has finished.' It clearly distinguishes itself from siblings by stating it is the 'only way' to learn what happened to a job, and cross-references copy_project and delete_project as producers of the job_id.

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?

Explicit when-to-use guidance is provided: 'call it after copy_project or delete_project and wait for a terminal state before reporting an outcome.' It also names alternatives for verification (get_project / list_projects) and warns about the 404 ambiguity, giving clear context on how to interpret results.

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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