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This skill should be used when the user sends an image and asks to "analyze this image", "describe this picture", "what's in this image", or any request requiring visual understanding of images. Provides image analysis using Zhipu GLM-4.6V multimodal model.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | glm-vision |
| description | This skill should be used when the user sends an image and asks to "analyze this image", "describe this picture", "what's in this image", or any request requiring visual understanding of images. Provides image analysis using Zhipu GLM-4.6V multimodal model. |
| version | 0.1.0 |
| disable-model-invocation | true |
| allowed-tools | ["Bash(*analyze_image*:*)"] |
使用智谱 GLM-4.6V 多模态模型分析图片内容。支持：
当用户发送图片并提出以下类型问题时触发：
需要设置 ZHIPU_API_KEY 环境变量：
export ZHIPU_API_KEY="your-api-key-here"
或者在 ~/.claude/settings.json 中配置：
{
"env": {
"ZHIPU_API_KEY": "your-api-key-here"
}
}
| 模型 | 用途 | 价格 |
|---|---|---|
glm-4.6v-flash | 免费版，日常使用 | 免费 |
glm-4.6v | 旗舰版，复杂推理 | 付费 |
glm-4.6v-flashx | 轻量高速版 | 付费 |
默认使用 glm-4.6v-flash 免费模型。
scripts/analyze_image.py \
--image "/path/to/image.jpg" \
--prompt "请描述这张图片" \
[--model "glm-4.6v-flash"]
参数说明：
--image / -i: 图片路径（支持 URL 或本地文件）--prompt / -p: 分析提示词--model / -m: 模型名称（可选，默认免费版）--detail / -d: 启用详细思考模式import base64
from openai import OpenAI
client = OpenAI(
api_key=os.environ.get("ZHIPU_API_KEY"),
base_url="https://open.bigmodel.cn/api/paas/v4"
)
# 读取本地图片
with open("image.jpg", "rb") as f:
img_base64 = base64.b64encode(f.read()).decode("utf-8")
response = client.chat.completions.create(
model="glm-4.6v-flash",
messages=[{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": img_base64}},
{"type": "text", "text": "请描述这张图片"}
]
}]
)
print(response.choices[0].message.content)
response = client.chat.completions.create(
model="glm-4.6v-flash",
messages=[{
"role": "user",
"content": [
{"type": "image_url", "image_url": {"url": "https://example.com/image.jpg"}},
{"type": "text", "text": "分析这张图片"}
]
}]
)
scripts/analyze_image.py \
-i "/tmp/screenshot.png" \
-p "描述这张截图的内容"
scripts/analyze_image.py \
-i "/tmp/photo.jpg" \
-p "分析这张图片的构图、色彩和主题" \
--detail
scripts/analyze_image.py \
-i "/tmp/document.png" \
-p "提取图片中的所有文字，保持原有格式"
scripts/analyze_image.py \
-i "https://example.com/image.jpg" \
-p "这张图片展示的是什么？"
references/api-reference.md - 完整 API 参考文档scripts/analyze_image.py - 图片分析辅助脚本Use the `bilibili-api-python` async library (400+ endpoints) for any Bilibili programmatic operation — videos, users, favorites, danmaku, live rooms, comments, search, uploads. This skill should be used whenever user asked for any Bilibili operation.
Fetch authoritative, current, version-specific documentation for libraries, SDKs, APIs, and CLI tools via Context7. MUST TRIGGER before writing or editing any non-stdlib library call — including well-known libraries you think you know, since your prior knowledge may be stale. SKIP for internal/private libraries, stdlib code, raw HTTP/filesystem, shell built-ins, or stable primitives whose signatures haven't changed in years (e.g. `json.dumps`, `os.path`). Prefer this over web search for library docs.
Query AI-generated overview of GitHub repositories via DeepWiki MCP. Use when needing a fast high-level understanding of a repository's architecture and design decisions without fetching full repository.
Periodic distillation: scan the last 5 days of high-quality Claude transcripts in the current project, dedup facts seen across sessions and against existing docs, and propose surgical edits to the right reference docs. Wider-than-daily window avoids 00:00 boundary loss. This skill should be used when the user says "distill recent", "distill session", "distill last week", or asks "what should we learn from recent work".
Extract atomic flashcards from documents/conversations and write them into local Anki via AnkiConnect, using a React-rendered paper-note card template with markdown, collapsible code, KaTeX, and mermaid. Triggers on "flashcards", "flash", "抽认卡", "anki".
Code search across millions of public GitHub repositories via grep.app. This skill should be used before writing or planning code. Use it to get real-world usage examples of libraries, frameworks, APIs, algorithms, or syntax patterns; to verify idiomatic usage; to find production patterns; or to explore how others solved similar problems. Prefer this over web search for code examples.