agentleFS
Starr-delStarr-del/ShipSafe/skills/rollback-readiness/SKILL.md

rollback-readiness

Skill0 starsChanged 5 months agoMITView on GitHub

Score how safely a project can be deployed AND rolled back — the final pre-push check. Use whenever the user says they're about to deploy, ship, launch, or push to production, asks 'is this ready to deploy', finishes a feature destined for prod, or at the end of any session that produced deployable changes. Run this proactively; it is the capstone check of the preflight pack. Runs fully offline — no API keys, no network, no credentials.

  • Reads credentials

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    All paths below are relative to this skill's directory (rollback-readiness/).

    line 25

≈ “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

rollback-readiness

Part of shipsafe — offline deploy-safety skills. Every script is stdlib-only Python 3.8+; nothing leaves the machine.

python3 scripts/readiness.py <project_root> [--json]

Runs 8 weighted checks and emits PASS/WARN/FAIL per check plus a 0–100 readiness score: health endpoint exists · env documented in .env.example · lockfile committed · migrations reversible · no committed secrets (quick pass) · runtime version pinned · deploy CI has concurrency control · README has run/deploy instructions.

Score bands: ≥80 ready · 60–79 fix FAILs first · <60 deploying now means debugging in production.

This skill is the entry point to the rest of the pack — each FAIL maps to a deeper skill (secrets → secret-preflight, migrations → migration-reversibility, env → env-drift, CI → ci-workflow-doctor). Run the deep skill on whatever fails, fix, and rerun until the score clears 80.

The framing to give the user: the score measures whether the person paged at 2am — possibly future-you — can understand, redeploy, and roll back this project without you in the room.

Exit codes: 0 score ≥ 80, 1 below.

All paths below are relative to this skill's directory (rollback-readiness/).

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.