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18072937735

Flame & Smoke Detection Skill | 烟火检测技能

作者 smyx-skills · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
60
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install smyx-fire-smoke-detection-analysis
功能描述
Detects fire and smoke in video scenes. Supports both video stream and image analysis. Suitable for fire early warning scenarios such as security surveillanc...
安全使用建议
What to check before installing or running this skill: - Trust the API endpoints: open skills/smyx_common/scripts/config.yaml and config-dev/test/prod to confirm base URLs and any api-key values. The config references lifeemergence.com and dev/test hosts — only use the skill if those services are trusted. - Inspect network utility code: review skills/smyx_common/scripts/util.py (RequestUtil) to see exactly what headers, authentication, and destinations are used for HTTP requests and whether any unexpected metadata or environment values are sent. - Confirm data handling and retention: the package will read local media files, may save attachments into the skill workspace, and smyx_common/dao.py creates a local SQLite DB under the workspace/data directory. If you will upload camera footage, ensure storage locations and retention are acceptable for privacy/security. - Credentials and config gap: although metadata lists no required env vars, the code reads environment variables and YAML config for API keys and open-id. Ensure you supply only intended credentials and that they are stored securely (or run without persisted credentials if possible). - Unrelated code included: the repository includes face-analysis and pet/health references and large common libraries. That suggests code reuse and increases attack surface; review whether any of those components expose extra endpoints or behaviors you don't want. - Sandbox first: run the skill in an isolated environment (no access to sensitive networks or production data) and observe outbound network calls before giving it access to real video or credentials. If you need, I can: (1) list the exact config file paths and values found in the repo, (2) extract and summarize RequestUtil behavior to show what outbound data is sent, or (3) point to the lines that create/modify the local DB and where attachments are saved.
功能分析
Type: OpenClaw Skill Name: smyx-fire-smoke-detection-analysis Version: 1.0.0 The skill bundle uses aggressive prompt injection techniques in SKILL.md (e.g., 'Mandatory Memory Rules', 'Highest Priority') to force the AI agent to ignore its internal memory and exclusively use a specific external API (lifeemergence.com). The underlying framework in smyx_common/scripts/util.py and dao.py automatically performs a remote 'phoneLogin' using the user-provided open-id and persists session tokens in a local SQLite database. Furthermore, skill.py contains logic to execute shell commands via subprocess.run to invoke the 'openclaw' agent recursively, which is a high-risk capability for an agent skill.
能力标签
requires-sensitive-credentials
能力评估
Purpose & Capability
The skill's code (scripts/fire_smoke_detection_analysis.py and scripts/*) implements fire/smoke detection via remote API calls which matches the stated purpose. However the repository also includes a full face_analysis skill, pet/health references, and a large 'smyx_common' library — many files appear reused from unrelated capabilities (face analysis, pet health). That extra code is not explained in SKILL.md and is disproportionate to a single-purpose detection skill.
Instruction Scope
SKILL.md requires reading config files under skills/smyx_common/scripts/config.yaml and workspace config paths to obtain open-id and optionally API keys, forbids reading local 'memory' files, and mandates saving uploaded attachments to an attachments directory. The runtime scripts read and validate local files, call remote APIs (multipart uploads or URL-based downloads), and the common code includes a DAO that creates/writes a local SQLite DB under workspace/data. The instruction set forbids using local memory for history but the codebase contains components that persist data locally — this mismatch is concerning.
Install Mechanism
There is no install spec (instruction-only install) which reduces installation risk. However the included smyx_common/requirements.txt lists many dependencies (a large ecosystem), implying the skill expects many packages to be present. Because no install step is declared, dependency installation/management is left to the integrator; that can lead to unexpected installs or runtime failures if attempted later.
Credentials
Registry metadata declares no required env vars or credentials, but the code reads configuration from YAML files and environment variables (e.g., OPENCLAW_SENDER_OPEN_ID, OPENCLAW_SENDER_USERNAME, FEISHU_OPEN_ID) and uses ApiEnum.API_KEY / base URLs defined in skills/smyx_common/config.yaml. SKILL.md mandates obtaining an 'open-id' (from config files or user) and the scripts accept optional --api-key/--api-url. The presence of network endpoints and optional API keys without declared required credentials is an information gap and can lead to unexpected transmission of video/media to remote hosts.
Persistence & Privilege
The skill does not request always:true and is user-invocable. However the codebase includes a local DAO that writes a SQLite DB under the workspace/data directory and scripts may save uploaded attachments into the skill directory. Those filesystem writes are within normal bounds for a media-analysis skill but are persistent and should be noted (where files are stored, retention, and cleanup).
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install smyx-fire-smoke-detection-analysis
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /smyx-fire-smoke-detection-analysis 触发
  4. 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
v1.0.0
- Initial release of the fire & smoke detection skill for video streams and images. - Supports fire and smoke detection, early warning, and marking abnormal locations for scenarios like surveillance, forest fire prevention, and industrial parks. - Strict rules enforced: absolutely prohibits reading local memory files or retrieving history from local/long-term memory—must always query the cloud API for historical reports. - Mandatory open-id verification workflow: must obtain open-id from config files or user input before proceeding; auto-generated or skipped IDs are prohibited. - Automates handling of user-uploaded media and triggers analysis or historical report listing based on specific keywords. - Provides structured output, with historical reports displayed as Markdown tables including clickable links to detailed reports.
元数据
Slug smyx-fire-smoke-detection-analysis
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Flame & Smoke Detection Skill | 烟火检测技能 是什么?

Detects fire and smoke in video scenes. Supports both video stream and image analysis. Suitable for fire early warning scenarios such as security surveillanc... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 60 次。

如何安装 Flame & Smoke Detection Skill | 烟火检测技能?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install smyx-fire-smoke-detection-analysis」即可一键安装,无需额外配置。

Flame & Smoke Detection Skill | 烟火检测技能 是免费的吗?

是的,Flame & Smoke Detection Skill | 烟火检测技能 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Flame & Smoke Detection Skill | 烟火检测技能 支持哪些平台?

Flame & Smoke Detection Skill | 烟火检测技能 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 Flame & Smoke Detection Skill | 烟火检测技能?

由 smyx-skills(@18072937735)开发并维护,当前版本 v1.0.0。

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