用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/membranedev/application-skills --skill llama-ai命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
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基于 SOC 职业分类
正在显示 SKILL.md
| name | llama-ai |
| description | Llama AI integration. Manage Organizations. Use when the user wants to interact with Llama AI data. |
| compatibility | Requires network access and a valid Membrane account (Free tier supported). |
| license | MIT |
| metadata | {"author":"membrane","version":"1.0","categories":""} |
Llama AI is a platform that provides AI-powered solutions for generating and understanding natural language. It's used by businesses and developers to automate tasks like content creation, chatbots, and text analysis.
Official docs: https://llama.meta.com/docs/
This skill uses the Membrane CLI (npx @membranehq/cli@latest) to interact with Llama AI. Membrane handles authentication and credentials refresh automatically — so you can focus on the integration logic rather than auth plumbing.
npx @membranehq/cli@latest login --tenant
A browser window opens for authentication. After login, credentials are stored in ~/.membrane/credentials.json and reused for all future commands.
Headless environments: Run the command, copy the printed URL for the user to open in a browser, then complete with npx @membranehq/cli@latest login complete <code>.
npx @membranehq/cli@latest search llama-ai --elementType=connector --json
Take the connector ID from output.items[0].element?.id, then:
npx @membranehq/cli@latest connect --connectorId=CONNECTOR_ID --json
The user completes authentication in the browser. The output contains the new connection id.When you are not sure if connection already exists:
npx @membranehq/cli@latest connection list --json
If a Llama AI connection exists, note its connectionIdWhen you know what you want to do but not the exact action ID:
npx @membranehq/cli@latest action list --intent=QUERY --connectionId=CONNECTION_ID --json
This will return action objects with id and inputSchema in it, so you will know how to run it.
Use npx @membranehq/cli@latest action list --intent=QUERY --connectionId=CONNECTION_ID --json to discover available actions.
npx @membranehq/cli@latest action run --connectionId=CONNECTION_ID ACTION_ID --json
To pass JSON parameters:
npx @membranehq/cli@latest action run --connectionId=CONNECTION_ID ACTION_ID --json --input "{ \"key\": \"value\" }"
When the available actions don't cover your use case, you can send requests directly to the Llama AI API through Membrane's proxy. Membrane automatically appends the base URL to the path you provide and injects the correct authentication headers — including transparent credential refresh if they expire.
npx @membranehq/cli@latest request CONNECTION_ID /path/to/endpoint
Common options:
| Flag | Description |
|---|---|
-X, --method | HTTP method (GET, POST, PUT, PATCH, DELETE). Defaults to GET |
-H, --header | Add a request header (repeatable), e.g. -H "Accept: application/json" |
-d, --data | Request body (string) |
--json | Shorthand to send a JSON body and set Content-Type: application/json |
--rawData | Send the body as-is without any processing |
--query | Query-string parameter (repeatable), e.g. --query "limit=10" |
--pathParam | Path parameter (repeatable), e.g. --pathParam "id=123" |
You can also pass a full URL instead of a relative path — Membrane will use it as-is.
npx @membranehq/cli@latest action list --intent=QUERY (replace QUERY with your intent) to find existing actions before writing custom API calls. Pre-built actions handle pagination, field mapping, and edge cases that raw API calls miss.