Agent skill

Vastai Local Dev Loop

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Build a fast local development loop that promotes a CPU-tested change to one disposable Vast.ai GPU canary and always tears it down.

MITAuto-check passedDevOps & Cloud

Install Vastai Local Dev Loop

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill vastai-local-dev-loop -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace vastai-local-dev-loop --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/vastai-local-dev-loop .claude/skills/vastai-local-dev-loop && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
vastai-local-dev-loop
GitHub stars
2.8k
Token cost
~1k tokens
SKILL.md length
437 words
Files
2 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Build a fast local development loop that promotes a CPU-tested change to one disposable Vast.ai GPU canary and always tears it down.

  • Works in 6 steps: Define the local contract → Run local gates → Publish immutable bytes → …
  • Iterating on images
  • SKILL.md covers Overview, Prerequisites, Instructions and Authentication, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Vastai Local Dev Loop is an agent skill from jeremylongshore/tons-of-skills-marketplace. Build a fast local development loop that promotes a CPU-tested change to one disposable Vast.ai GPU canary and always tears it down. Use when iterating on images, startup scripts, or training code. Trigger with: "test locally then on Vast.ai", "build a GPU canary loop", "shorten Vast.ai iteration".

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/official-docs.md`). Compatibility notes: Requires local container tooling, the Vast.ai CLI, a registry, a scoped API key, and a disposable GPU budget.

It sits in DevOps & Cloud, covering Deployment. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Iterating on images
  • Startup scripts
  • With: test locally then on Vast.ai
  • Build a GPU canary loop

Example prompts

  • “test locally then on Vast.ai”
  • “build a GPU canary loop”
  • “shorten Vast.ai iteration”
  • “/vastai-local-dev-loop”

Requirements

  • Docker
  • Compatibility (from SKILL.md): Requires local container tooling, the Vast.ai CLI, a registry, a scoped API key, and a disposable GPU budget.
  • Pre-approved tools (allowed-tools): Read, Grep, Write, Edit

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Define the local contract
  2. Run local gates
  3. Publish immutable bytes
  4. Rent the smallest canary
  5. Compare GPU behavior
  6. Tear down on every path

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Write
    • Edit

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • docs.vast.ai
    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Requires local container tooling, the Vast.ai CLI, a registry, a scoped API key, and a disposable GPU budget.

    From compatibility in the SKILL.md frontmatter.

Context cost

Vastai Local Dev Loop loads about 1k tokens when it runs, and up to ~1.3k if it reads all its reference files. Until then it costs about 80 tokens; SKILL.md has 437 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~80
When it runs · the whole SKILL.md, loaded when a task matches
~1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 437 words, ~1,007 tokens.

Download SKILL.mdSave it as .claude/skills/vastai-local-dev-loop/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
vastai-local-dev-loop
description
Build a fast local development loop that promotes a CPU-tested change to one disposable Vast.ai GPU canary and always tears it down. Use when iterating on images, startup scripts, or training code. Trigger with: "test locally then on Vast.ai", "build a GPU canary loop", "shorten Vast.ai iteration".
allowed-tools
Read, Grep, Write, Edit
compatibility
Requires local container tooling, the Vast.ai CLI, a registry, a scoped API key, and a disposable GPU budget.
version
2.0.0
argument-hint
[project-image-and-gpu-canary-policy]
model
inherit
effort
high
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, vastai, development, canary, containers

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.

Show full SKILL.md (185 more words)Show less

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

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in skills/.curated/vastai-local-dev-loop of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/official-docs.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Vastai Local Dev Loop next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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KubeSphere ServiceMesh Managerkubesphere/kubesphere17k—~2.4kAutomated safety check: PassCustom licence
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AWS Cdk Developmentzxkane/aws-skills3672 repos~2.5kAutomated safety check: PassMIT

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Categories

Questions about Vastai Local Dev Loop

What does Vastai Local Dev Loop do?

Build a fast local development loop that promotes a CPU-tested change to one disposable Vast.ai GPU canary and always tears it down. Vastai Local Dev Loop is an agent skill from jeremylongshore/tons-of-skills-marketplace.ai GPU canary and always tears it down.

When should I use Vastai Local Dev Loop?

Vastai Local Dev Loop fits situations like: iterating on images; startup scripts; with: test locally then on Vast.ai; build a GPU canary loop.

How do I install Vastai Local Dev Loop in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill vastai-local-dev-loop -a claude-code`. Or copy the skill folder (skills/.curated/vastai-local-dev-loop in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/vastai-local-dev-loop in your project. Claude Code loads it when a task matches its description.

How do I install Vastai Local Dev Loop in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill vastai-local-dev-loop -a codex`. Or copy the skill folder (skills/.curated/vastai-local-dev-loop in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/vastai-local-dev-loop in your project. Codex loads it when a task matches its description.

Can I use Vastai Local Dev Loop in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill vastai-local-dev-loop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/vastai-local-dev-loop, .gemini/skills/vastai-local-dev-loop, .github/skills/vastai-local-dev-loop and .opencode/skills/vastai-local-dev-loop in your project.

What does Vastai Local Dev Loop need to run?

SKILL.md names no scripts, command-line tools or credentials: Vastai Local Dev Loop is instructions for the agent only. Our summary lists: Docker. Its frontmatter pre-approves these tools: Read, Grep, Write, Edit. Compatibility (from SKILL.md): Requires local container tooling, the Vast.ai CLI, a registry, a scoped API key, and a disposable GPU budget..

Does Vastai Local Dev Loop access the network?

SKILL.md names 2 domains. As links in the text: docs.vast.ai and github.com. This is read from the text; nothing was executed.

Is Vastai Local Dev Loop safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Vastai Local Dev Loop use?

Vastai Local Dev Loop is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Vastai Local Dev Loop use?

About 1k tokens (SKILL.md is roughly 4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 339 tokens, read only when the agent opens those files.

What are the alternatives to Vastai Local Dev Loop?

Skills that share tags, products or a category with Vastai Local Dev Loop: Kubeshark Installer (kubeshark/kubeshark, 12k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars), KubeSphere ServiceMesh Manager (kubesphere/kubesphere, 17k stars) and Vercel (remotion-dev/remotion, 63k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Vastai Local Dev Loop?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.