Convex Backup

Organization

convex

convex-backup

Set up Convex backups and run a restore DRILL that proves recovery — snapshot, restore into a throwaway preview, assert the data came back — plus a schedule matched to your RPO and a gated recovery runbook.

Overview

Publisher	convex
Repository	`agent-skills`
Skill name	`convex-backup`
Stars	69
Forks	12
Bundled files	Instructions only
License	Apache-2.0
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by convex on GitHub. Read the source before you install it.

Installation

Install the Convex Backup AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/convex/agent-skills/tree/main/skills/convex-backup
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/convex/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/skills/convex-backup .claude/skills/convex-backup

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Convex Backup in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Convex Backup on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Convex Backup is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Back up — and prove the restore works

Every backup story has two halves and most people only do the first: taking the backup, and proving you can get it back. This capability does both — it sets up regular snapshot exports and then runs a RESTORE DRILL that actually recovers the data into a disposable preview and asserts it's intact. The drill reuses migrate-rehearse's exact primitives (snapshot export → preview deploy → snapshot import) pointed at recovery instead of a forward change, so the safety net is tested, not assumed.

Workflow

GUARD: deploy-guard — classify + announce the deployment being backed up (reading/exporting is safe; the drill's restore target is a throwaway preview, never prod).
TAKE the snapshot: npx convex export --path backup-<date>.zip (add --include-file-storage if the app stores files). This is the backup artifact; treat it as sensitive real data.
SCHEDULE it (the ongoing half): recommend a cadence matched to how fast the data changes and how much loss is tolerable (RPO) — e.g. a daily npx convex export via CI/cron to durable storage the user controls, with a retention window. Convex's own platform backups exist; this adds a user-owned, portable copy.
RESTORE DRILL (the half almost nobody does — this is the point): (a) PRECONDITION: a Preview Deploy Key as CONVEX_DEPLOY_KEY (same requirement as migrate-rehearse; a paid-tier feature). If unavailable, drill against a fresh personal dev deployment instead and say so. (b) create a throwaway preview from the CURRENT code: npx convex deploy --preview-create restore-drill-<date>. (c) restore the snapshot into it: npx convex import backup-<date>.zip --deployment restore-drill-<date> --replace (import targets a deployment by NAME with --deployment; there is no --preview-name on import). (d) ASSERT recovery: read the restored data back (MCP tables for row counts, data/runOneoffQuery for spot-checks) and confirm the critical tables came back with the expected row counts and a sample of real records — a restore that 'succeeds' but lands 0 rows is a FAILED drill. Compare against the source's counts where available.
REPORT the drill result plainly: what was backed up, that the restore was ACTUALLY performed and verified (or that it FAILED and why — a failed drill is the most valuable output, found before a real disaster), the recommended schedule + retention, and the recovery runbook (the exact commands to restore to prod: npx convex import backup.zip --replace --prod, gated by deploy-guard, with the post-snapshot-write-loss caveat stated).
HYGIENE: delete local snapshot copies when done (real data); the drill preview auto-expires. Never commit a backup file.

Rules

A backup you have never restored is a hope, not a backup — always run (or offer to run) the restore DRILL, don't just take the export.
The drill restores into a THROWAWAY preview (or dev), never prod; the restore target and the backup source are different deployments.
Assert recovery, don't assume it: a restore that lands 0 rows is a FAILED drill — check critical-table row counts + a real-record sample against the source.
A FAILED drill is the most valuable output — surface it loudly; that's the whole reason to drill before a real disaster.
Schedule matched to RPO (how much data loss is tolerable); keep a user-owned portable copy alongside Convex's platform backups, with a retention window.
Snapshots are sensitive real data: delete local copies when done, never commit them; the restore-to-prod runbook is deploy-guard-gated with the post-snapshot-write-loss caveat stated.
Shares migrate-rehearse's snapshot+preview mechanics but aims them at RECOVERY, not a forward change — a forward schema change is migrate-rehearse.

Frequently asked questions

What does the Convex Backup AI skill do?

Why use Convex Backup on TypingMind?

Because you install it once and use it with any model. Convex Backup is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Convex Backup in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/convex/agent-skills/tree/main/skills/convex-backup. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Convex Backup?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Convex Backup?

As many as you like. As long as a model supports skills, you can use Convex Backup with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Convex Backup AI skill free?

Yes. It is published on GitHub by convex under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Back up — and prove the restore works

Workflow

Rules

Frequently asked questions

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