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near-ai-cloud

NEAR AI Cloud private inference and verification

Install / Use

npx skills add internet-court/internet-court-skill --skill near-ai-cloud

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

83/100

Supported Platforms

Universal

Our assessment of near-ai-cloud

near-ai-cloud scores 83/100 on our quality scale, 1239th of 2,569 Development & Engineering skills we index (top 49%).

Its SKILL.md is 4.9 KB long, well organised into 8 sections with 3 code examples: a solid amount of guidance for an agent.

With 6,129 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
18/20
Description
8/15
Adoption
16/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 38 days ago, so near-ai-cloud is actively maintained.
  • No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
  • Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

near-ai-cloud compared with similar skills

All 4 of these similar skills score higher than near-ai-cloud; compare them before choosing.

SkillScoreStarsUpdatedFormat
near-ai-cloud (this skill)by internet-court836.1k38d agoSKILL.md
Agent-Reachby Panniantong10085.6k11d agoCLAUDE.md
headroomby headroomlabs-ai10073.9ktodayCLAUDE.md
ai-job-searchby MadsLorentzen10044.0k6d agoCLAUDE.md
claude-howtoby luongnv8910041.7ktodayCLAUDE.md

Frequently asked questions

How do I install near-ai-cloud?
Run npx skills add internet-court/internet-court-skill --skill near-ai-cloud. The install tabs above show the steps for each supported agent.
Which AI agents does near-ai-cloud work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is near-ai-cloud safe to use?
It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is near-ai-cloud still maintained?
The repository was last updated 38 days ago, so near-ai-cloud is actively maintained.

name: near-ai-cloud description: NEAR AI Cloud private inference and verification. Use when integrating NEAR AI Cloud API for verifiable private AI inference, verifying model or gateway TEE attestation (NVIDIA NRAS, Intel TDX), verifying chat message signatures, implementing end-to-end encrypted chat, or using the OpenAI-compatible API with NEAR AI Cloud. metadata: author: near version: "1.0.0"

NEAR AI Cloud

Verifiable private AI inference through Trusted Execution Environments (TEEs). All inference runs inside Intel TDX confidential VMs with NVIDIA TEE GPUs — your data stays encrypted and isolated from infrastructure providers, model providers, and NEAR itself.

Quick Start

The API is OpenAI-compatible. Point any OpenAI SDK at https://cloud-api.near.ai/v1:

import openai

client = openai.OpenAI(
    base_url="https://cloud-api.near.ai/v1",
    api_key="YOUR_API_KEY"  # from cloud.near.ai dashboard
)

response = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-V3.1",
    messages=[{"role": "user", "content": "Hello, NEAR AI!"}]
)
print(response.choices[0].message.content)
import OpenAI from 'openai';

const openai = new OpenAI({
    baseURL: 'https://cloud-api.near.ai/v1',
    apiKey: 'YOUR_API_KEY',
});

const completion = await openai.chat.completions.create({
    model: 'deepseek-ai/DeepSeek-V3.1',
    messages: [{ role: 'user', content: 'Hello, NEAR AI!' }]
});
console.log(completion.choices[0].message.content);

How It Works

  • All inference runs inside Intel TDX confidential VMs with NVIDIA TEE GPUs
  • TLS terminates inside the TEE, not at a load balancer — prompts are never exposed in plaintext
  • TEEs generate cryptographic attestation proofs verifiable via NVIDIA NRAS and Intel TDX
  • Every chat response is signed by a key that never leaves the TEE
  • You can independently verify hardware attestation and bind it to message signatures

Verification Flow

1. Generate nonce
2. Request model attestation  →  get signing_address, nvidia_payload, intel_quote
3. Verify GPU attestation     →  submit nvidia_payload to NVIDIA NRAS, check JWT fields
4. Verify CPU attestation     →  verify intel_quote via dcap-qvl or TEE Explorer
5. Verify GPU-CPU binding     →  signing_address + nonce bound in TDX report data; same nonce in NRAS eat_nonce
6. Make chat request           →  use the API as normal
7. Fetch chat signature       →  GET /v1/signature/{chat_id}
8. Verify signature            →  recover signer, compare to attested signing_address

API Endpoints

Base URL: https://cloud-api.near.ai

| Endpoint | Method | Description | |----------------------------------------|--------|------------------------------------| | /v1/chat/completions | POST | OpenAI-compatible chat completions | | /v1/models | GET | List available models | | /v1/attestation/report?model={model} | GET | Model attestation (GPU + CPU) | | /v1/attestation/report | GET | Gateway attestation | | /v1/signature/{chat_id} | GET | Chat message signature |

Critical Knowledge

  • Base URL is https://cloud-api.near.ai/v1 — use with any OpenAI SDK
  • signing_algo can be ecdsa or ed25519
  • Nonce should be a random 64-char hex string (32 bytes) for attestation freshness
  • NRAS response is a two-part array: [["JWT", "..."], {"GPU-0": "..."}] — overall JWT + per-GPU JWTs
  • The signing_address from model attestation must match the address that signed chat messages
  • Chat signatures are persistent and can be queried at any time after completion

References

| Topic | File | |----------------------------------|----------------------------------------------------------------------| | Private vs Anonymised Models | references/private-vs-anonymised.md | | Model TEE verification | references/model-verification.md |

Planned:

  • Gateway verification (TDX attestation for the API gateway + source provenance)
  • Chat verification (request/response hashing + signature verification)
  • E2E encrypted chat (ECDH key exchange, AES-256-GCM / ChaCha20-Poly1305)
  • OpenAI compatibility (streaming, reasoning models, Files API)

Resources

  • NEAR AI Cloud: https://cloud.near.ai
  • Documentation: https://docs.near.ai/cloud/introduction
  • Verification Example: https://github.com/near-examples/nearai-cloud-verification-example
  • Full Verifier: https://github.com/nearai/nearai-cloud-verifier
  • NVIDIA NRAS API: https://docs.api.nvidia.com/attestation/reference/attestmultigpu_1
  • TEE Attestation Explorer: https://proof.t16z.com/
  • DCAP QVL (TDX verification): https://github.com/Phala-Network/dcap-qvl

Related Skills

View on GitHub
GitHub Stars6.1k
CategoryDevelopment
Updated1mo ago
Forks110

Languages

TypeScript

Trust signals

88/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

1 medium