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18072937735

Contactless Health Risk Screening Tool | 非接触式健康风险检测分析工具

by smyx-skills · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install smyx-contactless-health-risk-detection-analysis
Description
Combines frontal facial image capture with multimodal physiological feature analysis to provide early risk screening and alerts for chronic and acute conditi...
Usage Guidance
Summary of practical concerns and steps before installing: - Data flows and privacy: This skill will accept facial images/videos and send them to remote APIs (base URLs found in smyx_common config point to lifeemergence.com domains). If you install it, highly sensitive biometric data will leave your machine — confirm you trust the remote service owner, their data retention and encryption practices, and that you have user consent. - Undeclared env/config access: The manifest claims no required env vars, but the code reads OPENCLAW_WORKSPACE, OPENCLAW_SENDER_OPEN_ID, OPENCLAW_SENDER_USERNAME, FEISHU_OPEN_ID and can read/write YAML config files (skills/smyx_common/scripts/config.yaml). Expect the skill to look at or create files under the workspace and to persist a local SQLite DB. If that surprises you, do not install. - Local persistence and writes: The skill will save attachments and may create a local DB under a workspace/data path and may create config YAML files if missing. Review those file locations and ensure they're acceptable for your environment (sandbox first). - Missing declaration of credentials: The code references API keys and has optional --api-key support but the registry lists no primary credential. Before use, determine what API endpoint and API key you must supply, who operates that endpoint, and how keys are stored and protected. - Medical/regulatory caution: This is a health-related tool that outputs screening suggestions. It explicitly says it is not a diagnosis. If you plan to deploy for real users (especially elderly or clinical settings), verify legal/regulatory compliance and clinical validation. - Recommended actions: - Inspect or grep the config files (skills/smyx_common/scripts/config*.yaml) to confirm the configured API base URLs and whether they point to a provider you trust. - Run the skill in a sandboxed environment (isolated workspace) first to observe files created under OPENCLAW_WORKSPACE and attachments/ and data/ so you can audit persistence. - If you cannot verify the remote API operator or data handling policies, do not use with real personal/biometric data. - If you need to proceed, require explicit consent from data subjects and prefer supplying an API key you control; review where and how the skill stores that key (config file) and secure it. What would change this assessment: providing an authoritative source/homepage for the skill and documentation from the API operator describing data handling, explicit manifest declarations of environment variables and file-write behavior, or removal of local DB/config creation would increase confidence. Conversely, evidence that the remote endpoints are untrusted or that the skill exfiltrates data beyond the described API would raise the verdict to malicious.
Capability Analysis
Type: OpenClaw Skill Name: smyx-contactless-health-risk-detection-analysis Version: 1.0.0 The skill implements a contactless health screening tool that captures facial images/videos and uploads them to a remote service (lifeemergence.com) for analysis. It contains aggressive prompt instructions in SKILL.md ('Forced Memory Rules') designed to override the AI agent's standard behavior by prohibiting the use of local memory and forcing cloud API usage. Technically, the bundle includes risky capabilities such as executing system commands via subprocess.run in skills/smyx_common/scripts/skill.py and storing authentication tokens/user identifiers in a local SQLite database (smyx-common-claw.db). While these actions appear aligned with the stated purpose of the tool, the combination of biometric data collection, forced API reliance, and system-level execution triggers a suspicious classification.
Capability Assessment
Purpose & Capability
The name and description (face-based, non-contact health risk screening) align with the included code: face_analysis and smyx_common modules implement API calls, file validation, and result formatting. That capability legitimately requires reading images and calling external AI APIs. However, the skill includes a local DAO (SQLite) and config management utilities that create/read config files and persist data under the workspace; these are not called out in the manifest or SKILL.md as expected behaviors, creating a mismatch between declared requirements and actual capabilities.
Instruction Scope
SKILL.md explicitly forbids reading local memory and long-term memory, yet the code provides DAO/SQLite logic, a path-based get_db_path that writes under ${OPENCLAW_WORKSPACE}/data, and logic that saves uploaded attachments to the skill's attachments directory. The runtime instructions require saving user uploads and calling remote APIs with images; those network calls are coherent with the purpose but involve transmitting highly-sensitive biometric data to external endpoints. The SKILL.md enforces strict open-id retrieval rules (via config files) but the code also reads environment variables (OPENCLAW_SENDER_OPEN_ID, OPENCLAW_SENDER_USERNAME, FEISHU_OPEN_ID) and will create or load YAML config files — behavior not declared in the manifest.
Install Mechanism
No install spec is provided (instruction-only plus bundled code). That reduces risk from downloading remote installers, but the repository contains requirements files (notably a very large smyx_common requirements.txt) implying many dependencies would be needed to run the code. There is no automatic download URL or extract step. Because the skill includes many Python modules but no declared package installation step, running it may fail or require installing many third-party packages manually.
Credentials
The registry metadata declares no required environment variables or credentials, but the code reads and uses several environment/config locations: OPENCLAW_WORKSPACE (used to derive DB and file paths), OPENCLAW_SENDER_OPEN_ID / OPENCLAW_SENDER_USERNAME / FEISHU_OPEN_ID in ConstantEnum.init, and optional API keys in smyx_common config.yaml. The SKILL.md demands open-id and prefers reading api-key from skills/smyx_common/scripts/config.yaml (or workspace-level config) — that means sensitive identifiers or keys may be sourced from local config files or environment variables even though the manifest did not declare them. This mismatch is disproportionate and undocumented.
Persistence & Privilege
The skill writes persistent data: it will save uploaded attachments to an attachments directory and the DAO creates/uses an SQLite DB under a workspace data directory. The Base Enum YAML loader will create missing config.yaml files. The skill does not request always:true, but it does create and modify files in workspace-related paths and may persist analysis records locally. Those filesystem writes and local DB creation are not highlighted in the manifest or the SKILL.md's prohibition of reading local memory, creating a privilege/persistence inconsistency the user should be aware of.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install smyx-contactless-health-risk-detection-analysis
  3. After installation, invoke the skill by name or use /smyx-contactless-health-risk-detection-analysis
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of the Contactless Health Risk Detection & Analysis skill. - Provides early-stage risk screening and alerts for chronic and acute conditions (e.g., heart attack, stroke, hypertension, hyperlipidemia) by analyzing frontal facial images with multimodal physiological features. - Supports both local image/video uploads and internet video/image URLs for analysis. - Enforces strict data handling and privacy rules, including prohibition on reading local memory files; all report queries must use the cloud API. - Requires users to provide an open-id (via config file or direct input) before analysis or report retrieval; operation is paused and prompts the user if open-id is not available. - Returns structured reports and outputs historical report lists in a Markdown table with direct links to each cloud-based report.
Metadata
Slug smyx-contactless-health-risk-detection-analysis
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Contactless Health Risk Screening Tool | 非接触式健康风险检测分析工具?

Combines frontal facial image capture with multimodal physiological feature analysis to provide early risk screening and alerts for chronic and acute conditi... It is an AI Agent Skill for Claude Code / OpenClaw, with 71 downloads so far.

How do I install Contactless Health Risk Screening Tool | 非接触式健康风险检测分析工具?

Run "/install smyx-contactless-health-risk-detection-analysis" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Contactless Health Risk Screening Tool | 非接触式健康风险检测分析工具 free?

Yes, Contactless Health Risk Screening Tool | 非接触式健康风险检测分析工具 is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Contactless Health Risk Screening Tool | 非接触式健康风险检测分析工具 support?

Contactless Health Risk Screening Tool | 非接触式健康风险检测分析工具 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Contactless Health Risk Screening Tool | 非接触式健康风险检测分析工具?

It is built and maintained by smyx-skills (@18072937735); the current version is v1.0.0.

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