Wikipedia:Tool apprenticeship

Tool apprenticeship is a proposed supplement to the current Wikipedia:Requests for adminship (RfA). Currently it is being proposed to run on a trial basis (details below).

In tool apprenticeship, a user who has a need for a particular administrator tool or tools, such as deletion or protection, makes a request to receive that tool. The user is judged according the the following criteria:

  • The user must be in good standing;
  • The user must have an ongoing need for the tool and be able to begin using it right away;
  • To the greatest extent possible, the user should be active and have sufficient experience in the area in which they plan to use the tool.

Satisfying these and following a consensus discussion, they receive the tool on a trial basis for a limited period (currently one week). When this period expires, the tool is automatically revoked. The trial period is subject to probation (tool revocation in case of misuse), and may involve voluntary mentoring.

After the end of their trial, the user can file a request for a new trial (also of one week), based on their performance during the trial period, which will be granted if the user substantially used the tool and exercised good judgement. If the request is denied, the user will be given extensive feedback on their usage and will have to demonstrate through their actions a clear understanding of that feedback before requesting a new trial.

Request for trials would be subject to a 7-day consensus discussion at Wikipedia:Requests for tool apprenticeship. Successful requests are closed by a bureaucrat, while an unsuccessful request can be closed by any experienced user in good standing. This discussion would be short and straightforward in most cases (similar to AfD) because less scrutiny is needed than for a full RfA: it's only granting a subset of tools for a limited period subject to probation. Irrelevant discussions that are not related to the tool or area under request are discouraged and may be hidden if they occur. "Conditional support" opinions, where a user agrees to support if the candidate agrees to their terms, help to avoid polarization.