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Intelligent Public Smoking Detection Skill | 公共场所吸烟行为智能检测技能
by
smyx-sunjinhui
· GitHub ↗
· v1.0.0
· MIT-0
64
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1
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Install in OpenClaw
/install smyx-smoking-detection-analysis
Description
Automatically detects smoking behavior in target areas based on computer vision; supports real-time detection of video streams, images, and video files; iden...
Capability Analysis
Type: OpenClaw Skill
Name: smyx-smoking-detection-analysis
Version: 1.0.0
The skill bundle exhibits several high-risk behaviors and architectural patterns. SKILL.md contains 'Mandatory Rules' designed to override the AI agent's default behavior by explicitly forbidding the use of local memory or LanceDB, which is a form of prompt injection used to control the agent's context. The common utility library (smyx_common/scripts/skill.py) includes an AgentSkill class that uses subprocess.run to execute the 'openclaw' command-line tool, creating a risk for recursive command injection. Furthermore, RequestUtil in util.py automatically handles user registration and token management by sending PII (like phone numbers provided as open-id) to external endpoints (lifeemergence.com) and storing credentials in a local SQLite database. While these features may support the cloud-based smoking detection service, the combination of subverting agent memory and providing shell execution capabilities is highly irregular.
Capability Tags
Capability Assessment
Purpose & Capability
The name/description (smoking detection via CV) matches the included code (scripts/smoking_detection_analysis.py and related API client code). Declared dependency on smyx_common is reasonable because shared APIs/config/utilities are used. However, the package bundle also contains a large 'face_analysis' subskill and a broad 'smyx_common' library (DB/DAO/config) that are not strictly necessary for a focused smoking-detection helper; their presence increases complexity and persistence surface.
Instruction Scope
SKILL.md mandates obtaining an open-id by reading config files in skills/smyx_common/scripts/config.yaml (and workspace-level config), requires saving uploaded attachments to a local attachments directory, and forbids reading local 'memory' files or LanceDB. The code does read config.yaml, sets ConstantEnum.CURRENT__OPEN_ID from passed args or environment, and will read and write files (including creating a local SQLite DB under workspace/data via the DAO utilities). The instructions force uploading media to a remote API (via RequestUtil/http_post), meaning user media is transmitted off-host. The prohibition on local memory access contrasts with the skill's use of other local config files and local DB utilities—this is inconsistent and should be clarified.
Install Mechanism
No install spec is provided (instruction-only), which is low-risk for automatic code fetching; however the repository contains many Python modules and a large requirements list in smyx_common/requirements.txt. Running the skill will require installing many dependencies (including network and DB libs). The lack of an install step means a user or operator will need to review and install dependencies manually in their environment—this elevates operational risk if done without inspection or sandboxing.
Credentials
The registry metadata shows no required env vars, but the code reads several environment variables implicitly: OPENCLAW_SENDER_OPEN_ID / OPENCLAW_SENDER_USERNAME / FEISHU_OPEN_ID (via ConstantEnum.init), and OPENCLAW_WORKSPACE is used to determine where DB/files are stored. The skill also expects/prohibits particular open-id values and requires an open-id to operate. The implicit use of workspace and sender env vars is not declared in the skill metadata, which is a proportionality / transparency problem. The skill will send uploaded media and request parameters to external API endpoints (configured in smyx_common config.yaml), so API keys, personal identifiers (open-id/username/phone), and media may be transmitted off-host.
Persistence & Privilege
The skill will create/use local persistence: it uses dao.py to initialize or access a SQLite DB under a data directory (derived from OPENCLAW_WORKSPACE or workspace path) and will save uploaded attachments to a skill attachments folder. The SKILL.md explicitly instructs saving attachments locally. The skill does not request 'always: true' and does not try to modify other skills' configurations, but it does read other-skill config files (skills/smyx_common/scripts/config.yaml) and can create local files and DBs—this is a non-negligible level of persistence and should be expected and consented to by the operator.
scan_findings_in_context
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install smyx-smoking-detection-analysis - After installation, invoke the skill by name or use
/smyx-smoking-detection-analysis - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of the smoking-detection-analysis skill for automated smoking behavior detection using computer vision.
- Supports real-time detection in video streams, images, and video files, identifying violations and triggering alerts.
- Strictly enforces usage of cloud interfaces for historical report queries—local memory or cache retrieval is prohibited.
- Requires open-id (from config or user) before processing any detection or report query; prohibits using defaults or guesses.
- Provides structured analysis reports and Markdown table output for history, including direct links to report images.
- Enforces dependencies and input/output formats for reliable, secure smoking detection and management workflow.
Metadata
Frequently Asked Questions
What is Intelligent Public Smoking Detection Skill | 公共场所吸烟行为智能检测技能?
Automatically detects smoking behavior in target areas based on computer vision; supports real-time detection of video streams, images, and video files; iden... It is an AI Agent Skill for Claude Code / OpenClaw, with 64 downloads so far.
How do I install Intelligent Public Smoking Detection Skill | 公共场所吸烟行为智能检测技能?
Run "/install smyx-smoking-detection-analysis" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Intelligent Public Smoking Detection Skill | 公共场所吸烟行为智能检测技能 free?
Yes, Intelligent Public Smoking Detection Skill | 公共场所吸烟行为智能检测技能 is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Intelligent Public Smoking Detection Skill | 公共场所吸烟行为智能检测技能 support?
Intelligent Public Smoking Detection Skill | 公共场所吸烟行为智能检测技能 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Intelligent Public Smoking Detection Skill | 公共场所吸烟行为智能检测技能?
It is built and maintained by smyx-sunjinhui (@smyx-sunjinhui); the current version is v1.0.0.
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