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在 OpenClaw 中安装
/install minor-detection
功能描述
当用户或上层系统需要判断聊天记录中的说话者是否可能是未成年人、青少年、中学生、高中生，或需要对单会话、多会话历史做年龄倾向、校园倾向、学生画像、未成年人风险与证据分析时使用此技能。即使用户没有直接说“未成年人识别”，但需求本质上是判断“像不像未成年用户”、输出未成年人概率、画像、趋势、风险等级或结构化证据，也应激...
安全使用建议
This skill will send the conversation text, timestamps, prior profile, and other metadata to whatever classifier and embedding endpoints you configure via env vars — ensure MINOR_DETECTION_CLASSIFIER_BASE_URL points to a trusted service and use a dedicated, least-privilege API key. If you require fully local processing, do not set the remote classifier/embedding env vars. Make sure the runtime environment provides requests/httpx/numpy (the bundled code expects them) or the pipeline will fail. Note the registry only declared the base URL and API key as required; the skill will also honor many optional config env vars (model, timeouts, embedding keys) — review and set those as needed. If you have confidentiality/regulatory constraints (sensitive user data, underage detection), consider running this code in a controlled environment or using a provider you trust before enabling it.
能力评估
Purpose & Capability
Name/description (minor/age-detection) match the code and runtime behavior. The script bundle implements payload normalization, optional retrieval, classifier calls, schema repair, and post-processing — all consistent with a minor-detection pipeline. The two required env vars (classifier base URL and API key) are appropriate and declared as primary.
Instruction Scope
SKILL.md enforces calling the control script and returning its single JSON output. The control script will transmit conversation text, timestamps, historical profile and metadata to the configured remote classifier endpoint and (optionally) to an embedding endpoint. That external transmission is explicit in the docs and expected for this skill, but it means user data (full conversation and metadata) will leave the host when classifier/embedding env vars are set.
Install Mechanism
There is no install spec (instruction-only for the platform), but the skill bundles multiple Python scripts. Nothing is downloaded from arbitrary URLs or installed during platform install. Runtime requires Python libraries (requests, httpx, numpy) to be present; lacking them will cause runtime errors.
Credentials
Registry-required env vars are MINOR_DETECTION_CLASSIFIER_BASE_URL and MINOR_DETECTION_CLASSIFIER_API_KEY (primary) — which is proportionate. SKILL.md and config.py also read many optional environment variables (model, timeout, retries, embedding base/key/model, SKILL_EMBEDDING_*, timezone, retrieval_top_k). Those additional env vars are optional and reasonable for configuring behavior, but they were not all listed in the registry 'requires.env' block — the discrepancy is informational and worth noting.
Persistence & Privilege
Skill does not request always:true and does not modify other skills or system settings. It runs as an invoked script and does not request elevated platform privileges. Autonomous invocation is allowed by default but is not combined with other privilege escalations.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install minor-detection - 安装完成后，直接呼叫该 Skill 的名称或使用
/minor-detection触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v0.1.5
- 移除了对 MINOR_DETECTION_EMBEDDING_BASE_URL 和 MINOR_DETECTION_EMBEDDING_API_KEY 的强制依赖配置，仅保留了分类相关的必需环境变量。
- 精简了元数据和环境依赖的说明，使依赖项与实际需求一致。
- 其余内容和调用流程保持不变。
v0.1.4
- 添加了对 MINOR_DETECTION_EMBEDDING_BASE_URL 和 MINOR_DETECTION_EMBEDDING_API_KEY 环境变量的声明与要求
- 明确 embedding 检索相关的环境变量依赖配置
- 其余行为、规则与执行流程无变化
v0.1.3
- Added explicit metadata fields specifying required environment variables and primary environment variable.
- Clarified that remote model and embedding interfaces must be explicitly configured; default values are no longer assumed.
- Updated external service and privacy explanation to emphasize explicit endpoint and credential configuration requirements.
- Minor documentation improvements for clarity; no code logic or file changes.
v0.1.2
- Documentation fully rewritten in Chinese to clarify usage scenarios, contract, input preparation, execution steps, and privacy/external service notes.
- Notable detail changes: no support for `OPENAI_API_KEY` or `OPENAI_BASE_URL` environment variables; added `SKILL_EMBEDDING_*` vars to the environment list.
- Expanded usage guidance: skill should be activated for any scenario involving minor or student profile/age/risk detection, even if not asked explicitly.
- No changes to code or logic; documentation updates only.
v0.1.1
- Updated documentation to clarify privacy, remote API usage, credential handling, and data routing details.
- Added explicit section on external services, default endpoints, and relevant environment variables.
- Revised description and instructions for greater clarity and conciseness.
- No changes to code or logic in this release.
v0.1.0
Initial release of minor-detection skill.
- Provides a structured process for detecting whether chat participants may be minors.
- Runs the official detection pipeline and returns only its JSON output without modification.
- Enforces strict input, execution, and output rules to ensure compliance and consistency.
- Designed for use in both single- and multi-session analyses of user conversations.
元数据
常见问题
minor-detection 是什么？
当用户或上层系统需要判断聊天记录中的说话者是否可能是未成年人、青少年、中学生、高中生，或需要对单会话、多会话历史做年龄倾向、校园倾向、学生画像、未成年人风险与证据分析时使用此技能。即使用户没有直接说“未成年人识别”，但需求本质上是判断“像不像未成年用户”、输出未成年人概率、画像、趋势、风险等级或结构化证据，也应激... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 160 次。
如何安装 minor-detection？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install minor-detection」即可一键安装，无需额外配置。
minor-detection 是免费的吗？
是的，minor-detection 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
minor-detection 支持哪些平台？
minor-detection 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 minor-detection？
由 张潇涵（@xiaohanzhang2005）开发并维护，当前版本 v0.1.5。
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