poe-chat
使用 @gemini/@gpt/@claude 等触发词调用 Poe 模型(含 Gemini/GPT/claude/kimi/Deepseek等主流模型),自动选择 model_id 并说明使用了哪一个,支持文件上传。
Install
mkdir -p .claude/skills/poe-chat && curl -L -o skill.zip "https://mcp.directory/api/skills/download/6944" && unzip -o skill.zip -d .claude/skills/poe-chat && rm skill.zipInstalls to .claude/skills/poe-chat
About this skill
Poe Chat Skill
适用场景
- 用户输入包含
@gemini、@gpt等 @触发词,希望用 Poe 上的具体模型回答问题。 - 需要自动匹配最合适的具体模型名称(例如 gemini-3-flash)。
- 支持把本地文件上传给模型分析。
使用方式
1) 安装依赖(只需一次)
pip install -r scripts/requirements.txt
如系统没有 python 命令,请改用 python3 执行下列命令。
2) 设置 Poe API Key(如未设置)
export POE_API_KEY="your_api_key"
也可以在调用时通过 --api-key 传入(优先生效)。
3) 查看可用模型(独立脚本)
python scripts/list_models.py
默认会在当前目录生成精简版 models.json(仅包含 id),并作为本地缓存(缓存时间 1 小时,基于文件修改时间)。
也可指定输出文件名:
python scripts/list_models.py --out models.json
如需查看完整模型信息(如 description 等),使用 --full:
python scripts/list_models.py --full --out models-full.json
4) 根据模型列表选择模型 ID
从 models.json 中选择要使用的模型 ID:
- 重点字段是
data[].id(这就是model_id) - 可结合
data[].description判断用途和能力
示例(手动选择):
{
"data": [
{"id": "gemini-3-pro", "description": "..."},
{"id": "claude-opus-4.6", "description": "..."}
]
}
当用户输入 @gemini ... 时,选择包含 Gemini 的模型,并遵循以下优先级:
- 默认优先非 Pro(例如优先
gemini-3-flash而不是gemini-3-pro) - 优先最新版本号(例如 2.5 优于 2.0)
- 只有用户明确要求 Pro/Ultra 时才选 Pro/Ultra(例如用户输入
@gemini-pro或明确说“用Pro”)
5) 调用脚本(直接传入模型 ID)
python scripts/poe_client.py \
--message "请解释量子计算" \
--model-id "gemini-3-flash" \
--api-key "your_api_key" \
--file "/path/to/document.pdf"
说明:
--message必填,内容中包含@xxx触发词即可(如 @gemini、@gpt)。--file可选,可重复多次上传多个文件。
行为准则
- 解析触发词:从用户消息中提取第一个
@xxx触发词。 - 模型选择:根据
models.json里的data[].id手动选择最相关的具体模型。 - 模型列表:通过
list_models.py获取模型列表,内存缓存 1 小时(不持久化)。 - API Key:若环境变量
POE_API_KEY未设置,poe_client.py会提示用户输入。 - 文件上传:如提供
--file,poe_client.py使用fastapi-poe上传并附加到请求。 - 响应输出:回答正文前必须标注 具体模型名(例如
Model used: gemini-3-flash)。
输出格式
Model used: <具体模型名>
<模型回答内容>
如存在模型返回的附件,列出附件信息(名称、类型、URL)。
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