VA

vastai-local-dev-loop

Sets up a fast, reproducible local development loop for Vast.ai GPU projects to minimize cloud costs.

Install

mkdir -p .claude/skills/vastai-local-dev-loop && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/5336" && unzip -o skill.zip -d .claude/skills/vastai-local-dev-loop && rm skill.zip

Installs to .claude/skills/vastai-local-dev-loop

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Configure Vast.ai local development with testing and fast iteration.
68 charsno explicit “when” trigger
Intermediate

Key capabilities

  • →Structure projects with API clients and job runners
  • →Mock Vast.ai API responses for unit testing
  • →Test Docker images locally in CPU mode
  • →Verify CLI authentication and account balance
  • →Implement dry-run workflows for training scripts

How it works

It establishes a local development loop by mocking the Vast.ai API and using Docker to simulate the containerized environment. This allows developers to validate logic and job orchestration without incurring cloud GPU costs.

Inputs & outputs

You give it
Training code and Dockerfile
You get back
Verified local development environment and mocked test suite

When to use vastai-local-dev-loop

  • →Setting up local development environments
  • →Testing GPU job provisioning
  • →Mocking Vast.ai API for fast iteration

About this skill

Vast.ai Local-to-GPU Canary Loop

Overview

Keep slow marketplace operations out of the inner loop. Validate code and the container locally, publish an immutable image, then use a single policy-constrained GPU rental only for the behavior that cannot be proven without CUDA.

Prerequisites

  • Local unit and CPU-mode test commands with expected outputs
  • Immutable image registry and a reproducible startup contract
  • Canary GPU, price, reliability, timeout, and cleanup policy

Instructions

Step 1: Define the local contract

Use Read and Grep to identify entrypoints, required files, ports, and environment names. Write an explicit smoke command that works without cloud credentials.

Step 2: Run local gates

Execute unit tests, build the image, start it in CPU mode where supported, and validate its health or process exit contract.

Step 3: Publish immutable bytes

Push a digest or commit-addressed image. Reject mutable latest as canary evidence because the remote host may pull different bytes.

Step 4: Rent the smallest canary

Search verified offers within the budget, create one instance with the immutable image, and record the contract ID before polling.

Step 5: Compare GPU behavior

Run the same smoke assertion plus a CUDA-specific check. Capture structured output and the image digest, not interactive screenshots.

Step 6: Tear down on every path

Copy only the required evidence, destroy the instance, and confirm removal even when the canary fails.

Authentication

Inject the scoped Vast.ai key only into the local control process. Put workload secrets in an approved runtime secret mechanism and never bake them into the image or startup script.

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

  • Local test/build receipt and immutable image identity
  • GPU canary offer, instance, state, and assertion evidence
  • Confirmed teardown plus a classified local/remote delta

Return commit, image digest, offer and instance IDs, local/GPU outcomes, elapsed time, estimated cost, and cleanup status.

Examples

A model-server change passes CPU request-shape tests, is pushed by digest, then runs one CUDA inference on a verified low-cost GPU before the disposable contract is destroyed.

Error Handling

FailureResponse
Local smoke failsDo not rent a GPU; fix the deterministic local failure first.
Remote bytes differDestroy the canary and republish an immutable digest.
GPU assertion fails only remotelyCollect driver, CUDA, image, and command evidence before teardown.
Teardown is uncertainTreat the instance as actively billable and escalate with its ID.

Resources

When not to use it

  • →Testing code that requires actual GPU hardware acceleration
  • →Performance benchmarking on CPU-only environments

Prerequisites

Completed vastai-install-auth setupDocker installed locallyPython 3.8+ with pytest

Limitations

  • →Local testing uses CPU mode which may not catch GPU-specific errors
  • →Mock return values must be manually updated if the API interface changes

How it compares

It shifts testing from the cloud to a local containerized environment, reducing costs and iteration time compared to deploying to a remote GPU instance for every change.

Compared to similar skills

vastai-local-dev-loop side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
vastai-local-dev-loop (this skill)12moReviewIntermediate
documenso-local-dev-loop22moReviewBeginner
gentleman-e2e18moReviewIntermediate
nx-run-tasks18moNo flagsIntermediate

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