agentleFS
learntocloudlearntocloud/learn-to-cloud-app/.github/skills/reset-prod-submissions/SKILL.md

reset-prod-submissions

Skill1.1k starsChanged 59 days agoMITView on GitHub

Reset a user's production verification attempts after preview and explicit confirmation. Use for "reset prod submissions", "undo prod verification", or "reset prod for <username>".

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 0 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Delete only the previewed scope in one transaction using the same predicates.

    line 18
  2. Very specific:

    Use RETURNING id and verify the remaining count before commit.

    line 19
  3. Very specific:

    Do not use the retired submissions or verification_jobs tables.

    line 23

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Reset Production Submissions

This is a destructive production operation. Use the connection procedure and firewall cleanup rules from query-prod-db.

  1. Resolve the GitHub username through users; do not use remembered IDs.
  2. Resolve any requested requirement slug to its UUID from the current curriculum artifact.
  3. Preview matching rows from verification_attempts, including id, requirement_uuid, outcome, and timestamps. Scope by user_id and, unless resetting everything was explicit, requirement_uuid.
  4. Show the exact count and scope, then obtain explicit user confirmation.
  5. Delete only the previewed scope in one transaction using the same predicates. Use RETURNING id and verify the remaining count before commit.
  6. Re-query after commit and report the deleted and remaining counts.

Progress is derived from verification_attempts; no counter requires updating. Do not use the retired submissions or verification_jobs tables. Do not broaden a requirement-scoped reset to all attempts. If the schema, username, or slug cannot be resolved unambiguously, stop without deleting.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.