Agent skill · Backend & API

ai-chat

Access 50+ LLM models through a unified OpenAI-compatible API via AceDataCloud. Use when you need chat completions from GPT, Claude, Gemini, DeepSeek, Grok, or other models through a single endpoint. Supports streaming, function calling, and vision.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill ai-chat-acedatacloud-skills-2 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 5 KB
Bundled scripts: none
Version: 1.0
Declared author: acedatacloud
Requires: Requires ACEDATACLOUD_API_TOKEN environment variable. Works as a drop-in replacement for the OpenAI SDK.
Path: skills/ai-llm/ai-chat-acedatacloud-skills-2/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# AI Chat — Unified LLM Gateway Access 50+ language models through a single OpenAI-compatible endpoint via AceDataCloud. ## Authentication ```bash export ACEDATACLOUD_API_TOKEN="your-token-here" ``` ## Quick Start ```bash curl -X POST https://api.acedata.cloud/v1/chat/completions \ -H "Authorization: Bearer $ACEDATACLOUD_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{"model": "claude-sonnet-4-20250514", "messages": [{"role": "user", "content": "Hello!"}]}' ``` ## OpenAI SDK Drop-in ```python from openai import OpenAI client = OpenAI( api_key="your-token-here", base_url="https://api.acedata.cloud/v1" ) response = client.chat.completions.create( model="gpt-4.1", messages=[{"role": "user", "content": "Explain quantum computing"}] ) print(response.choices[0].message.content) ``` ## Available Models ### OpenAI GPT | Model | Type | Best For | |-------|------|----------| | `gpt-4.1` | Latest | General-purpose, high quality | | `gpt-4.1-mini` | Small | Fast, cost-effective | | `gpt-4.1-nano` | Tiny | Ultra-fast, lowest cost | | `gpt-4o` | Multimodal | Vision + text | | `gpt-4o-mini` | Small multimodal | Fast vision tasks | | `o1` | Reasoning | Complex reasoning tasks | | `o1-mini`

What's inside
Steps it walks through
  1. Authentication
  2. Quick Start
  3. OpenAI SDK Drop-in
  4. Available Models
  5. OpenAI GPT
  6. Anthropic Claude
  7. Google Gemini
  8. DeepSeek
  9. xAI Grok
  10. Features
  11. Streaming
  12. Function Calling
  13. Vision
  14. Parameters
Ships with 1 file
  • metadata.json
Commands it runs
export ACEDATACLOUD_API_TOKEN="your-token-here"
curl -X POST https://api.acedata.cloud/v1/chat/completions \
More from claude-skill-registry
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About this skill
What does the ai-chat skill do?

Access 50+ LLM models through a unified OpenAI-compatible API via AceDataCloud. Use when you need chat completions from GPT, Claude, Gemini, DeepSeek, Grok, or other models through a single endpoint. Supports streaming, function calling, and vision.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill ai-chat-acedatacloud-skills-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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