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Agent Skill · 研究检索

vastai-api(vastai API 搜索)

用于辅助 API 设计、接口文档、请求响应结构和服务集成说明。它适合让 Agent 梳理 endpoint、生成 OpenAPI 草稿、检查字段命名、整理错误码或辅助前后端联调。使用时需要确认真实业务语义、鉴权方式、分页和错误处理规则;涉及生成接口文档时,应避免凭空补字段,最好从现有代码、schema 或接口样例中提取事实。

vastai-api 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证为 MIT,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 42,497。

总安装 1,069周安装 45GitHub Stars 31下载 374核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:vastai-api(vastai API 搜索)
来源仓库:https://github.com/rawveg/skillsforge-marketplace
仓库路径:skills/vastai-api
安装命令:
npx skills add https://github.com/rawveg/skillsforge-marketplace --skill vastai-api
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/rawveg/skillsforge-marketplace --skill vastai-api

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于辅助 API 设计、接口文档、请求响应结构和服务集成说明,适合梳理 endpoint、生成 OpenAPI 草稿或检查字段命名。它可帮助整理错误码、分页规则或前后端联调要点,但不能凭空补字段。通过 npx skills add 命令从指定仓库安装,具体用法需结合 README 进一步确认。

使用时需确认真实业务语义、鉴权方式和操作边界,避免依赖虚构数据。vastai-api 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/vastai-api

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/rawveg/skillsforge-marketplace --skill vastai-…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

vastai-api 怎么安装?

在终端执行 npx skills add https://github.com/rawveg/skillsforge-marketplace --skill vastai-api。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

vastai-api 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

vastai-api 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

vastai-api 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

vastai-api 用的人多吗?

公开数据是累计安装 1,069 次,近一周安装 45 次,下载 374 次,GitHub 31 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

vastai-api 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
vastai-api

vastai API 搜索 · 本页

1,06931接触敏感数据MIT未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Vastai-Api Skill

Comprehensive assistance with the Vast.ai API for managing GPU instances, machine operations, and automating AI/ML workflows. This skill provides access to official documentation for programmatically controlling the Vast.ai platform.

When to Use This Skill

This skill should be triggered when working with:

  • GPU Instance Management: Creating, destroying, starting, stopping, or managing GPU instances
  • Machine Operations: Listing machines for rent, setting pricing, managing maintenance windows
  • SSH & Authentication: Managing SSH keys, API keys, and secure connections to instances
  • Billing & Credits: Viewing invoices, earnings, deposits, or transferring credits
  • Network Volumes: Creating, listing, or managing network storage volumes
  • Serverless Endpoints: Working with Vast.ai serverless workergroups and endpoints
  • Data Transfer: Copying data between instances or cloud services
  • Account Management: Managing subaccounts, environment variables, or team roles
  • CLI Operations: Using the vastai command-line tool
  • API Integration: Building applications that integrate with Vast.ai's REST API

Quick Reference

Creating and Managing Instances

Create a New GPU Instance
# Create instance from an offer
vastai create instance <offer_id> \
  --image pytorch/pytorch:latest \
  --disk 50 \
  --ssh
List Your Active Instances
# Show all instances
vastai show instances

# Show specific instance details
vastai show instance <instance_id>
Manage Instance State
# Stop an instance (pause GPU billing, storage still charged)
vastai stop instance <instance_id>

# Start a stopped instance
vastai start instance <instance_id>

# Reboot instance without losing GPU priority
vastai reboot instance <instance_id>

# Destroy instance permanently (irreversible)
vastai destroy instance <instance_id>

SSH Key Management

Add SSH Key to Account
# Add your public SSH key
vastai create ssh-key "ssh-rsa AAAAB3NzaC1yc2EA... user@host"

# List all SSH keys
vastai show ssh-keys

# Attach SSH key to specific instance
vastai attach ssh <instance_id> <ssh_key>

Search and Filter Offers

Search for GPU Offers
# Search with filters
vastai search offers \
  --gpu_name RTX_4090 \
  --num_gpus 2 \
  --disk_space 100

# Order by price
vastai search offers --order dph_total

Environment Variables (Secrets)

Manage Environment Variables
# Create encrypted environment variable
vastai create env-var MY_API_KEY "secret_value_here"

# List all environment variables
vastai show env-vars

# Update existing variable
vastai update env-var MY_API_KEY "new_secret_value"

# Delete environment variable
vastai delete env-var MY_API_KEY

Billing and Credits

View Billing Information
# Show invoices
vastai show invoices

# Show earnings (for hosts)
vastai show earnings

# Show deposit for specific instance
vastai show deposit <instance_id>

# Transfer credits to another user
vastai transfer credit recipient@email.com 25.00

Instance Logs

Retrieve Container Logs
# Get last 100 lines of logs
vastai show logs <instance_id> --tail 100

# Filter logs with grep pattern
vastai show logs <instance_id> --filter "error"

# Get daemon system logs
vastai show logs <instance_id> --daemon-logs

Data Transfer Operations

Copy Between Instances
# Copy from one instance to another
vastai copy <src_id> <dst_id> /source/path /destination/path

# Cloud copy using rclone
vastai cloud copy <instance_id> remote:bucket/path /local/path

Machine Management (for Hosts)

List Your Machine for Rent
# List machine with pricing
vastai list machine <machine_id> \
  --price_gpu 0.50 \
  --price_disk 0.10

# Unlist machine (stop renting)
vastai unlist machine <machine_id>

# Schedule maintenance window
vastai schedule maint <machine_id> \
  --sdate "2025-11-01T10:00:00" \
  --duration 3600

Key Concepts

Instance Types

  • On-Demand Instances: Pay-as-you-go GPU instances you create and manage
  • Interruptible Instances: Lower-cost instances that can be reclaimed by hosts
  • Reserved Instances: Pre-paid instances with usage discounts (up to 40%)

Pricing Model

  • GPU Pricing: Charged per hour while instance is running
  • Storage Pricing: Charged for disk space even when instance is stopped
  • Network Transfer: Upload/download bandwidth costs
  • Discounts: Available through prepayment on reserved instances

Instance States

  • starting: Instance is initializing
  • running: Instance is active and billable
  • stopped: Container stopped (storage still billable)
  • exited: Container exited or failed
  • rebooting: In process of restarting
  • recycling: Being destroyed and recreated from fresh image

Authentication

  • API Keys: Used for programmatic access via REST API
  • SSH Keys: For secure shell access to running instances
  • Environment Variables: Encrypted secrets injected into containers

Templates

Pre-configured setups containing:

  • Docker image specifications
  • Environment variables
  • Onstart scripts
  • Resource requirements
  • Port mappings

Popular templates include PyTorch, TensorFlow, Jupyter, ComfyUI, and Stable Diffusion.

Network Volumes

Shared network storage that can be:

  • Attached to multiple instances
  • Persisted independently of instance lifecycle
  • Used for datasets and model weights
  • Scaled independently

Serverless Architecture

  • Endpoints: Top-level routing and configuration
  • Workergroups: Pools of GPU instances that autoscale
  • Test Workers: Exploration phase for performance profiling
  • Target Utilization: Controls scaling behavior

Reference Files

This skill includes comprehensive documentation in references/:

llms-full.md

Complete API reference with all endpoints organized by category:

  • Accounts: API keys, SSH keys, user management, subaccounts
  • Billing: Invoices, earnings, deposits, credit transfers
  • Instances: Create, manage, destroy, reboot, logs, SSH
  • Machines: List for rent, pricing, maintenance, default jobs
  • Network Volumes: Create, list, manage shared storage
  • Search: Find offers, benchmarks, filter GPU availability
  • Serverless: Endpoints, workergroups, autoscaling configuration

Each endpoint includes:

  • HTTP method and path
  • Detailed description
  • CLI usage examples
  • Parameter specifications
  • Source documentation links

llms-txt.md

Focused documentation covering:

  • Serverless workergroup parameters and configuration
  • Endpoint management
  • QuickStart guide with setup instructions
  • Common questions and answers
  • Schema.org structured data for better searchability

llms.md

Curated list of all API operations with brief descriptions and CLI examples, organized by category for quick lookup.

Working with This Skill

For Beginners

Start here:

  1. Review the QuickStart section in llms-txt.md
  2. Follow the 4-step setup process (signup, add credit, prepare SSH, create instance)
  3. Try the basic examples in Quick Reference above
  4. Learn about instance states and pricing model in Key Concepts

First tasks to try:

  • Create an API key for authentication
  • Add your SSH public key to your account
  • Search for available GPU offers
  • Create your first instance with a template

For Intermediate Users

Focus on:

  • Environment variable management for secrets
  • Data transfer between instances and cloud storage
  • Instance lifecycle management (stop/start/reboot vs destroy)
  • Billing optimization with reserved instances
  • Custom template creation for your workflows

Useful patterns:

  • Set up auto-billing to avoid instance interruptions
  • Use environment variables for API keys and credentials
  • Schedule regular backups with copy commands
  • Monitor costs with invoice and earnings endpoints

For Advanced Users

Advanced topics:

  • Serverless endpoint and workergroup configuration
  • Machine hosting and marketplace optimization
  • Network volume architecture for shared datasets
  • Team and subaccount management
  • API integration in custom applications
  • Automated scaling strategies

Power user tips:

  • Use filter operators in search (eq, neq, gt, lt, gte, lte, in, nin)
  • Leverage launch_args for advanced instance customization
  • Implement monitoring and alerting via logs API
  • Optimize costs with bid price adjustments
  • Build workflows with cloud copy for data pipelines

Navigation Tips

Finding API endpoints:

  • All endpoints documented in llms-full.md with full details
  • Organized by category (accounts, billing, instances, machines, etc.)
  • Each includes CLI usage examples

Quick lookups:

  • llms.md provides condensed list of all operations
  • Use browser search (Ctrl+F) to find specific commands
  • Look for "CLI Usage:" sections for command syntax

Understanding concepts:

  • Key Concepts section above for terminology
  • QuickStart in llms-txt.md for getting started
  • Workergroup Parameters section for serverless configuration

Common Workflows

Setting Up a New Development Environment

  1. Create API key with appropriate permissions
  2. Add SSH key to account for access
  3. Create environment variables for secrets
  4. Search for GPU offers matching requirements
  5. Create instance from template
  6. Connect via SSH and verify setup

Managing Long-Running Training Jobs

  1. Create instance with sufficient disk space
  2. Set up auto-billing to prevent interruptions
  3. Use reserved instance with prepayment for discounts
  4. Monitor with logs endpoint
  5. Copy model checkpoints to cloud storage
  6. Stop (not destroy) when paused to save costs

Hosting Machines for Profit

  1. Set machine pricing with list command
  2. Define minimum bid thresholds
  3. Configure default jobs for background work
  4. Schedule maintenance windows when needed
  5. Monitor earnings and clean up expired contracts
  6. Adjust pricing based on market conditions

Best Practices

Cost Management

  • Destroy vs Stop: Use stop for short pauses, destroy for long breaks
  • Disk Space: Choose carefully - cannot be changed later
  • Reserved Instances: Prepay for 40% discount on long-running work
  • Auto-billing: Set threshold above daily spend to prevent interruptions
  • Low Balance Alerts: Enable email notifications as backup

Security

  • API Keys: Use permission scoping, rotate regularly
  • SSH Keys: Use different keys for different purposes
  • Environment Variables: Store secrets as encrypted env vars
  • Subaccounts: Use for team members with restricted access

Performance

  • Template Caching: Pre-pulled images start much faster (seconds vs minutes)
  • Network Volumes: Use for large datasets shared across instances
  • Bid Pricing: Higher bids get better hardware availability
  • Test Workers: Let serverless explore before scaling

Reliability

  • Logs: Monitor regularly for errors
  • Health Checks: Implement in your applications
  • Data Backup: Copy critical data off instances regularly
  • Redundancy: For critical work, run on multiple instances

Resources

Official Links

Support

  • Minimum deposit: $5
  • Balance shown at top right of dashboard
  • Email verification required to rent or create teams
  • Auto-billing prevents interruptions when configured

Notes

  • This skill was automatically generated from official Vast.ai documentation
  • Reference files preserve structure and examples from source docs
  • CLI examples use the vastai command-line tool
  • API endpoints support both REST API and CLI access
  • All prices in USD, billed per hour for compute and storage

Updating

To refresh this skill with updated documentation:

  1. Re-run the scraper with the same configuration
  2. The skill will be rebuilt with the latest API information
  3. Check for API version changes or deprecated endpoints

平台分布

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按下载量换算106

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22.49%
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windsurf

15.78%
按下载量换算59

trae

12.08%
按下载量换算45

Codex

6.75%
按下载量换算25

OpenCode

3.43%
按下载量换算13

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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