Skip to content
Back to skills

Vastai Core Workflow A

ASecurity

Analyze and execute a checkpointed Vast.ai training job from offer policy through artifact recovery and destruction. Use when a repeatable single-job GPU run needs budget and interruption controls. Trigger with: "run training on Vast.ai", "checkpoint a Vast.ai job", "recover Vast.ai training artifacts".

  • 2,719 stars
  • 0 votes
  • 0 copies
  • 0 views
  • Added September 21, 2026
ai-agentsgo

Works with

  • terminal

Security analysis

A100/100

Pro scans all 2 files and shows the line behind each finding

Scanned September 21, 2026

npx -y skills add jeremylongshore/claude-code-plugins-plus --skill vastai-core-workflow-a --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Vastai Core Workflow A?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Vastai Core Workflow A
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/jeremylongshore-vastai-core-workflow-a-6a861991/badge)](https://www.skillsdirectory.com/skills/jeremylongshore-vastai-core-workflow-a-6a861991)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: vastai-core-workflow-a
description: >-
  Analyze and execute a checkpointed Vast.ai training job from offer policy through artifact recovery and destruction. Use when a repeatable single-job GPU run needs budget and interruption controls. Trigger with: "run training on Vast.ai", "checkpoint a Vast.ai job", "recover Vast.ai training artifacts".
allowed-tools: Read, Grep, Write, Edit
version: 2.0.0
argument-hint: '[training-command-gpu-policy-and-checkpoint-target]'
model: inherit
effort: high
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
  - saas
  - vastai
  - training
  - checkpoints
  - instances
compatibility: 'Requires an immutable training image, reachable checkpoint storage, a scoped Vast.ai key, and an approved GPU budget.'
---

# Checkpointed Vast.ai Training Run

## Overview

Treat a training run as a recoverable state machine, not an SSH session. Bind code and image identity, select an offer through policy, persist checkpoints outside the disposable root disk, export final evidence, and destroy.

## Prerequisites

- Immutable image and code revision with deterministic training command
- GPU, VRAM, disk, reliability, geography, and price policy
- Checkpoint destination, resume test, runtime deadline, and cleanup owner

## Instructions

### Step 1: Freeze the run manifest

Record code revision, image digest, dataset version, command, seed, expected checkpoint cadence, budget, and output destination.

### Step 2: Select and create

Search only verified rentable offers that meet the manifest, record price components, and create one labeled instance. Persist `new_contract` immediately.

### Step 3: Reach readiness safely

Poll structured instance state with a deadline and terminal branches. Confirm image identity, disk headroom, GPU model, and CUDA visibility.

### Step 4: Run with external checkpoints

Start the workload so checkpoints are uploaded or copied to durable storage at the declared cadence. A local checkpoint alone is not recovery evidence.

### Step 5: Verify completion or resume

Validate artifact checksums and run metadata. For an interruption, provision a replacement from policy and prove resume from the last durable checkpoint.

### Step 6: Close the cost boundary

Copy final logs and checksums, destroy the instance, confirm removal, and reconcile actual spend against the manifest.

## Authentication

Use a scoped control-plane key for search and instance operations. Give the workload only the storage credential needed for its checkpoint prefix, with no Vast.ai billing or team authority.

## Tool Discipline

Use Read and Grep to inspect manifests, configuration, provider output, and existing tests before proposing a mutation. Use Write or Edit only for the approved plan, implementation, test, or redacted receipt; do not create, update, destroy, or fund Vast.ai resources without explicit operator approval.

## Output

- Frozen run and offer-selection manifest
- State, checkpoint, resume, artifact, and spend evidence
- Confirmed instance destruction and discrepancy report

Return revision, image digest, offer and instance IDs, checkpoint URI/checksum, terminal result, actual spend, and cleanup confirmation.

## Examples

A fine-tuning job checkpoints every ten minutes to a run-specific object prefix; after a simulated interruption, a replacement instance resumes from the last checksum and the original contract is destroyed.

## Error Handling

| Failure | Response |
| --- | --- |
| No compliant offer exists | Pause the run and report the binding constraint; do not silently weaken reliability or price policy. |
| Checkpoint upload fails | Stop training before the recovery window is exceeded and repair storage access. |
| Host goes offline | Use the last external checkpoint on a different host and preserve the affected instance ID for support. |
| Artifact checksum fails | Do not mark the run complete; retain evidence and rerun from the last verified checkpoint. |

## Resources

- [First-party source notes](references/official-docs.md)
- [Instance overview](https://docs.vast.ai/guides/instances/overview)
- [Data movement](https://docs.vast.ai/guides/instances/storage/data-movement)
- [Manage instances](https://docs.vast.ai/guides/instances/manage-instances)

Files in this skill

  • SKILL.md4.2 KB
  • references/official-docs.md1.3 KB

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.