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Credit Code Cert Ocr
by
SCNet-sugon
· GitHub ↗
· v1.0.3
· MIT-0
111
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3
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Install in OpenClaw
/install credit-code-cert-ocr
Description
将图片中的文字、统一社会信用代码证书等信息识别并提取出来。本技能应在用户需要 OCR 识别图片中的文字,或识别统一社会信用代码证书时使用。
README (SKILL.md)
\r
Sugon-Scnet 统一社会信用代码证书 OCR 技能\r
\r 本技能封装了 Sugon-Scnet 统一社会信用代码证书 OCR 服务,通过单一接口即可调用 1 种识别能力,高效提取文字及票据信息。\r \r
功能特性\r
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- 行业资质:统一社会信用代码证书。\r \r
前置配置\r
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⚠️ 重要:使用前需要申请 Scnet API Token\r \r
申请 API Token\r
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- 访问 Scnet 官网 注册/登录\r
- 在控制台申请 API 密钥(格式:
sc-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx)\r - 复制密钥备用\r \r
配置 Token\r
\r 手动配置(推荐)\r
- 在技能目录下创建
config/.env文件,内容如下:\r
# ===== Sugon-Scnet OCR API 配置 =====\r
# 申请地址:https://www.scnet.cn\r
SCNET_API_KEY=your_scnet_api_key_here\r
\r
# API 基础地址(一般无需修改)\r
SCNET_API_BASE=https://api.scnet.cn/api/llm/v1\r
```\r
2. 添加:`SCNET_API_KEY=你的密钥`\r
3. 设置文件权限为 600(仅所有者可读写)\r
**⚠️ 安全警告**:切勿将 API Key 直接粘贴到聊天对话中,否则可能被记录或泄露。\r
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### Token 更新\r
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Token 过期后调用会返回 401 或 403 错误。更新方法:重新申请 Token 并替换 config/.env 中的 SCNET_API_KEY。\r
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### 依赖安装\r
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本技能需要 Python 3.6+ 和 requests 库。请运行以下命令:\r
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```bash\r
pip install requests\r
```\r
---\r
### 使用方法\r
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### 参数说明\r
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| 参数名 | 类型 | 必填 | 描述 |\r
|--------|------|------|------|\r
| ocrType | string | 是 | 识别类型枚举。必须为以下之一:\x3Cbr>• UNIFIED_SOCIAL_CREDIT_REG(统一社会信用代码证书) |\r
| filePath | string | 是 | 待识别图片的本地绝对路径。支持 jpg、png、pdf 等常见格式。 |\r
\r
### 命令行调用示例\r
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```bash\r
python .claude/skills/credit_code_cert_ocr/scripts/main.py UNIFIED_SOCIAL_CREDIT_REG /path/to/invoice.jpg\r
```\r
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### 在 AI 对话中使用\r
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用户可以说:\r
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- “帮我识别这张统一社会信用代码证书,图片在 /Users/name/Downloads/id.jpg”\r
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AI 会根据 description 中的关键词自动触发本技能。\r
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### AI 调用建议\r
为避免触发 API 速率限制(10 QPS),请串行调用本技能,即等待前一个识别完成后再发起下一个请求。\r
如果使用 OpenClaw 的 exec 工具,建议设置 timeout 或 yieldMs 参数,让命令同步执行,避免多个命令同时运行导致并发。\r
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### 配置选项\r
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编辑 `config/.env` 文件:\r
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| 变量名 | 默认值 | 说明 |\r
|--------|--------|------|\r
| SCNET_API_KEY | 必需 | Scnet API 密钥 |\r
| SCNET_API_BASE | https://api.scnet.cn/api/llm/v1 | API 基础地址(一般无需修改) |\r
\r
### 输出\r
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- 标准输出:识别结果的 JSON 数据,结构与 API 文档一致,位于 `data` 字段内。\r
- 识别结果位于 data[0].result[0].elements 中,具体字段取决于 ocrType。\r
- 错误信息:如果发生错误,会输出以 `错误:` 开头的友好提示。\r
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### 注意事项\r
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- 本技能调用的 OCR API 有 10 QPS 的速率限制。\r
- 如果遇到 429 错误,请等待 2-3 秒后重试,不要连续发起请求。\r
- 建议在调用前确保图片已准备就绪,避免因网络问题导致重复调用。\r
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### 故障排除\r
\r
| 问题 | 解决方案 |\r
|------|----------|\r
| 配置文件不存在 | 创建 config/.env 并填入 Token(参考前置配置) |\r
| API Key 无效/过期 | 重新申请 Token 并更新 `.env` 文件 |\r
| 文件不存在 | 检查提供的文件路径是否正确 |\r
| 网络连接失败 | 检查网络连接或防火墙设置 |\r
| 不支持的文件类型 | 确保文件扩展名为允许的类型(参考 API 文档) |\r
| 401/403/Unauthorized | Token 无效或过期,重新申请并配置 |\r
| 429 Too Many Requests | 请求过于频繁,技能会自动等待并重试(最多 3 次)。若持续失败,请降低调用频率或联系服务方提高限额。 |\r
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Usage Guidance
This skill appears to do what it claims: it uploads a local image to Scnet's OCR API and returns structured JSON. Before installing, verify the publisher and repository (skill.yaml points to a GitHub URL placeholder), and be aware you must provide SCNET_API_KEY — the skill will send the image and any extracted text to api.scnet.cn. Do not paste your API key into chat; store it in config/.env or an environment variable and set file permissions (chmod 600). If the images contain sensitive data, consider privacy implications of sending them to an external OCR service or test on non-sensitive samples first. Also ask the skill author/maintainer to fix the packaging metadata so required_env_vars/primary_credential are consistently declared in the registry.
Capability Analysis
Type: OpenClaw Skill
Name: credit-code-cert-ocr
Version: 1.0.3
The skill is a legitimate OCR tool for identifying Unified Social Credit Code certificates using the Sugon-Scnet API (api.scnet.cn). The Python script (scripts/main.py) correctly handles file uploads, implements standard retry logic for rate limiting, and follows security best practices by advising users to store API keys in environment variables or protected config files rather than sharing them in chat.
Capability Tags
Capability Assessment
Purpose & Capability
The name/description (OCR for unified social credit certificates) align with the code and SKILL.md: the script reads a local image and uploads it to https://api.scnet.cn/api/llm/v1/ocr/recognize. However the registry metadata (in the evaluation header) reported no required env vars or primary credential while the included SKILL.md and skill.yaml declare SCNET_API_KEY as required — this is a packaging/metadata inconsistency that should be corrected.
Instruction Scope
Runtime instructions and scripts are narrowly scoped: they read a local config/.env (or env var) for SCNET_API_KEY, read the specified filePath, and POST it to the documented Scnet OCR endpoint. They do not attempt to read unrelated system files or credentials.
Install Mechanism
No install spec is provided (instruction-only packaging) and the included Python script depends on standard requests and python3. The README/SKILL.md ask users to pip install requests — low risk. No archived downloads or external installers are used.
Credentials
The script only requires SCNET_API_KEY (and optionally SCNET_API_BASE), which is proportional to calling a third‑party OCR API. The inconsistency is that the registry metadata shown to the evaluator claimed no required env vars/primary credential; the true package requires an API key. Confirming the declared required env var in the registry UI is recommended.
Persistence & Privilege
The skill does not request persistent/always-on privileges, does not modify other skills, and runs only when invoked. It only reads its own config/.env and the user-supplied image file.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install credit-code-cert-ocr - After installation, invoke the skill by name or use
/credit-code-cert-ocr - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.3
- Added skill.yaml configuration file.
- Updated documentation with explicit required/optional environment variables.
- Clarified security best practices: recommend not pasting API Key into chat and setting config file permissions.
- Added explicit dependency instructions for Python and requests.
- Refined usage documentation for accuracy and conciseness.
v1.0.1
No user-facing changes in this version.
- Version bump to 1.0.1; no code or documentation updates detected.
- All existing features, behavior, and documentation remain the same.
v0.1.0
Initial release of credit_code_cert_ocr skill:
- Recognizes and extracts text from images, especially unified social credit code certificates, via OCR.
- Requires Scnet API Token configuration before first use.
- Supports command-line and conversational usage; works with common image formats (jpg, png, pdf).
- Returns structured JSON output with recognition results and confidence scores.
- Includes rate limit handling (10 QPS) and detailed troubleshooting tips.
Metadata
Frequently Asked Questions
What is Credit Code Cert Ocr?
将图片中的文字、统一社会信用代码证书等信息识别并提取出来。本技能应在用户需要 OCR 识别图片中的文字,或识别统一社会信用代码证书时使用。 It is an AI Agent Skill for Claude Code / OpenClaw, with 111 downloads so far.
How do I install Credit Code Cert Ocr?
Run "/install credit-code-cert-ocr" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Credit Code Cert Ocr free?
Yes, Credit Code Cert Ocr is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Credit Code Cert Ocr support?
Credit Code Cert Ocr is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Credit Code Cert Ocr?
It is built and maintained by SCNet-sugon (@scnet-sugon); the current version is v1.0.3.
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