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Agent Skill · 开发

running-claude-code-via-litellm-copilot(running Claude 代码 VIA litellm GitHub Copilot)

running-claude-code-via-litellm-copilot 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

running-claude-code-via-litellm-copilot 是开发类 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;许可证信息还不明确,第三方扫描有未通过项,按安装量在开发类的 21,746 个 Skill 里排第 18。

总安装 1,941,264周安装 79,316GitHub Stars 40下载 621,712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
unknown

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:running-claude-code-via-litellm-copilot(running Claude 代码 VIA litellm GitHub Copilot)
来源仓库:https://github.com/xixu-me/skills
仓库路径:skills/running-claude-code-via-litellm-copilot
安装命令:
npx skills add https://github.com/xixu-me/skills --skill running-claude-code-via-litellm-copilot
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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/xixu-me/skills --skill running-claude-code-via-litellm-copilot

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

用于处理 GitHub 仓库、Issue、Pull Request 等协作信息。适合围绕仓库状态和代码变更进行整理。可结合来源仓库和安装命令进一步核验用法。建议确认权限范围及是否会触发联网或文件读写。

running-claude-code-via-litellm-copilot 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/running-claude-code-via-litellm-copilot

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/xixu-me/skills --skill running-claude-code-via…;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

running-claude-code-via-litellm-copilot 怎么安装?

在终端执行 npx skills add https://github.com/xixu-me/skills --skill running-claude-code-via-litellm-c…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

running-claude-code-via-litellm-copilot 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。

running-claude-code-via-litellm-copilot 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。

running-claude-code-via-litellm-copilot 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

running-claude-code-via-litellm-copilot 用的人多吗?

公开数据是累计安装 1,941,264 次,近一周安装 79,316 次,下载 621,712 次,GitHub 40 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。

running-claude-code-via-litellm-copilot 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。

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。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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。
  • 需要处理开发类任务、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。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
running-claude-code-via-litellm-copilot

running Claude 代码 VIA litellm GitHub Copilot · 本页

1,941,26440接触敏感数据未明确未通过

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

Overview

Use this skill for the specific workaround where Claude Code keeps its Anthropic-shaped client behavior, but the actual backend traffic is sent to a local LiteLLM proxy and then forwarded to GitHub Copilot.

Treat this as an advanced workaround, not an officially guaranteed GitHub workflow. Help the user succeed technically, but do not promise GitHub support, policy approval, or long-term compatibility.

This skill is guidance-first but execution-aware:

  • If the user wants explanation only, provide the smallest correct set of files, commands, and checks.
  • If the user wants real setup work on the current machine, inspect first and adapt commands to the active shell and OS.
  • Pause before persistent edits such as ~/.claude/settings.json or shell profile files.

Read references/doc-verified-notes.md before answering if you need to justify which parts come from the article and which parts were tightened against current LiteLLM docs.

When To Use

Use this skill when the user wants any of the following:

  • Claude Code to run against GitHub Copilot through LiteLLM
  • lower direct Anthropic API spending while keeping the Claude Code workflow
  • a local config.yaml for LiteLLM's GitHub Copilot provider
  • ANTHROPIC_BASE_URL, ANTHROPIC_MODEL, or CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC setup
  • help understanding GitHub device authorization during LiteLLM startup
  • help with model mismatch, 404-like errors, no requests reaching LiteLLM, or GitHub 401/403 failures

Do not use this skill for:

  • deciding whether the workaround is allowed by GitHub terms
  • general LiteLLM architecture unrelated to Claude Code plus Copilot
  • direct Anthropic API setup with no Copilot or LiteLLM component

Core Rules

  1. Lead with a short compliance caveat. Explain that this is a workaround based on a local proxy path, not a GitHub-promoted workflow, and the user must evaluate the latest Copilot terms and limits for themselves.
  2. Prefer the minimum viable path first. Start with temporary environment variables and a local config.yaml unless the user explicitly wants a persistent setup.
  3. Keep ANTHROPIC_MODEL and LiteLLM model_name identical. Exact string match matters more than clever explanation.
  4. Treat ANTHROPIC_AUTH_TOKEN as a local placeholder. Claude Code expects a non-empty value locally, but it is not the GitHub Copilot credential and should not be presented as a reusable secret.
  5. Never overwrite ~/.claude/settings.json wholesale. Merge only the needed env keys and preserve unrelated settings.

Workflow

1. Preflight

Check these first when the user wants real setup work:

  • claude --help succeeds
  • uv --version or pip --version succeeds
  • the user has GitHub Copilot access
  • the intended LiteLLM port is available, usually 4000

If the user only wants instructions, state the prerequisites instead of running them.

2. Choose Temporary vs Persistent Setup

Use this rule:

  • Temporary setup: preferred default for first-time setup, debugging, and low-risk trials
  • Persistent setup: only when the user explicitly wants the proxy path to apply every time Claude Code starts

For persistent setup, confirm the target file and then merge keys into ~/.claude/settings.json. Do not replace the file contents.

3. Create LiteLLM config.yaml

Start from the article's flow, but keep the provider naming aligned with LiteLLM docs:

model_list:
  - model_name: claude-opus-4.5
    litellm_params:
      model: github_copilot/claude-opus-4.5
      drop_params: true

Explain the fields:

  • model_name: the logical name Claude Code will request
  • model: the LiteLLM provider route, using github_copilot/<model>
  • drop_params: true: strips unsupported Anthropic-specific fields before forwarding to Copilot

If the user wants a different Copilot-backed model, keep the same pattern:

model_list:
  - model_name: <logical-name>
    litellm_params:
      model: github_copilot/<copilot-model>
      drop_params: true

Do not hardcode extra headers into the default path unless the user already hit a rejection that suggests header overrides are needed.

4. Install and Start LiteLLM

Preferred install:

uv tool install "litellm[proxy]"

Fallback:

pip install "litellm[proxy]"

Start the proxy from the directory containing config.yaml:

litellm --config config.yaml --port 4000

Tell the user to keep that terminal open because the logs are the fastest truth source during verification.

5. Explain GitHub Device Authorization

On the first successful request to the GitHub Copilot provider, LiteLLM may open a device authorization flow:

  1. LiteLLM prints a verification URL and device code
  2. the user opens the URL and approves the request
  3. LiteLLM stores the resulting credential locally for future use

Optional token-location overrides exist:

  • GITHUB_COPILOT_TOKEN_DIR
  • GITHUB_COPILOT_ACCESS_TOKEN_FILE

Only mention these when the user needs custom token storage, shared environments, or troubleshooting around expired or misplaced credentials.

6. Configure Claude Code

For a temporary PowerShell session:

$env:ANTHROPIC_AUTH_TOKEN = "sk-any-string"
$env:ANTHROPIC_BASE_URL = "http://localhost:4000"
$env:ANTHROPIC_MODEL = "claude-opus-4.5"
$env:CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC = "1"
claude

For a temporary Bash or Zsh session:

export ANTHROPIC_AUTH_TOKEN="sk-any-string"
export ANTHROPIC_BASE_URL="http://localhost:4000"
export ANTHROPIC_MODEL="claude-opus-4.5"
export CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC=1
claude

For persistent configuration, merge these keys into ~/.claude/settings.json:

{
  "env": {
    "ANTHROPIC_AUTH_TOKEN": "sk-any-string",
    "ANTHROPIC_BASE_URL": "http://localhost:4000",
    "ANTHROPIC_MODEL": "claude-opus-4.5",
    "CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC": "1"
  }
}

Merge-safe behavior:

  • if the file does not exist, create it
  • if it exists, preserve all unrelated top-level keys
  • preserve existing env entries that are unrelated to this workflow
  • update only the four keys above
  • if the JSON is malformed, stop and report the parse problem instead of overwriting the file

7. Verify The Request Chain

Use two terminals when possible:

  • Terminal A runs LiteLLM
  • Terminal B runs claude

Ask for one small prompt such as a short script or code review request, then verify:

  • Claude Code starts normally
  • LiteLLM logs show an inbound request
  • LiteLLM logs indicate the GitHub Copilot model route, typically github_copilot/<model>

The healthy path is:

Claude Code -> LiteLLM -> GitHub Copilot -> LiteLLM -> Claude Code

8. Troubleshooting

If Claude Code reports model-not-found, 404-like failures, or LiteLLM says the model does not exist:

  • compare ANTHROPIC_MODEL to model_name exactly
  • check case, punctuation, and hyphens

If LiteLLM never receives a request:

  • confirm ANTHROPIC_BASE_URL points to http://localhost:4000
  • confirm LiteLLM is still running on that port
  • confirm the environment variables were set in the same shell session that launched claude
  • check local firewall or port conflicts if the URL is correct but still silent

If LiteLLM reaches GitHub Copilot but gets 401 or 403 responses:

  • repeat the device authorization flow by restarting LiteLLM and retrying
  • confirm the GitHub account still has Copilot access
  • if custom token-directory variables are set, verify they point to the intended files

Advanced Fallback: Header Overrides

The article uses explicit Copilot-style headers. Current LiteLLM docs expose GitHub Copilot as a provider and also document header override support.

Only reach for explicit extra_headers when:

  • the basic provider flow reaches Copilot but still needs client-shape overrides
  • the user already has evidence that a specific environment behaves better with editor-style headers

Example fallback:

model_list:
  - model_name: claude-opus-4.5
    litellm_params:
      model: github_copilot/claude-opus-4.5
      drop_params: true
      extra_headers:
        editor-version: "vscode/1.85.1"
        editor-plugin-version: "copilot/1.155.0"
        Copilot-Integration-Id: "vscode-chat"
        user-agent: "GithubCopilot/1.155.0"

Present this as an advanced fallback, not the universal default.

Output Checklist

When answering a real user request with this skill, include:

  • the brief compliance caveat
  • the exact config.yaml or the delta to apply
  • shell-appropriate commands
  • whether the setup is temporary or persistent
  • the verification path
  • the smallest relevant troubleshooting section if something failed

Safety Reminders

  • Do not state that GitHub officially supports this workaround.
  • Do not imply that a dummy ANTHROPIC_AUTH_TOKEN is a real Copilot credential.
  • Do not recommend replacing ~/.claude/settings.json wholesale.
  • Do not present stale model names as guaranteed current availability; if the user asks for a specific model, keep the github_copilot/<model> pattern and note that Copilot-exposed model availability may change.

平台分布

Claude

32.3%
按下载量换算200,813

Codex

32.27%
按下载量换算200,626

Cursor

16.77%
按下载量换算104,261

Gemini CLI

10.2%
按下载量换算63,415

安全审计

Gen Agent Trust Hub

未通过

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。目前只有一个公开来源,建议同时核对源仓库。

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