LC Scene Analysis HTTP

v1.0.5

工地隐患分析模型技能,默认处理施工现场静态图片的隐患识别;仅在用户明确要求时调用数据采集或交叉验证接口。

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for chenqu108/lc-scene-analysis-http.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "LC Scene Analysis HTTP" (chenqu108/lc-scene-analysis-http) from ClawHub.
Skill page: https://clawhub.ai/chenqu108/lc-scene-analysis-http
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Required binaries: curl
Config paths to check: [object Object]
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install lc-scene-analysis-http

ClawHub CLI

Package manager switcher

npx clawhub@latest install lc-scene-analysis-http
Security Scan
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OpenClawOpenClaw
Benign
high confidence
Purpose & Capability
Name/description (工地隐患分析模型) match the runtime instructions: it calls three HTTP endpoints to perform analysis, data-collection, and cross-validation. Requiring curl and an auth profile with api_base/api_key is appropriate for this purpose.
Instruction Scope
SKILL.md confines behavior to static image analysis, specifies when to call each endpoint, and explicitly forbids unrelated actions (video streams, device control, local model inference). It also instructs not to reveal keys/tokens. There are no instructions to read unrelated system files or exfiltrate arbitrary data.
Install Mechanism
Instruction-only skill with no install spec and no code files — lowest install risk. It only requires curl to be present, which is reasonable for issuing HTTP requests.
Credentials
The skill requires an auth profile containing api_base and api_key (and flow_id/algorithm_id). That credential request is proportionate to calling a remote analysis API. However, the registry metadata is inconsistent/opaque: top-level shows 'Required config paths: [object Object]' and lists 'Required env vars: none' / 'Primary credential: none', which fails to clearly declare the needed profile/credential. This metadata mismatch reduces transparency and should be corrected.
Persistence & Privilege
always=false, user-invocable, and no install-time persistence. The skill does not request elevated/system-wide privileges or modify other skills' configs.
Assessment
This skill appears to do what it says: call a remote HTTP API to analyze construction-site images. Before installing, verify the auth profile and api_base are correct and trusted (ensure api_base points to a domain you control or a reputable provider). Restrict the api_key to minimal scope and treat it as a secret (store it in the platform's secure config). Ask the publisher to fix the registry metadata (the 'Required config paths' blob and version mismatch) so it's explicit that an auth profile with api_key is required. Consider testing with non-sensitive images first and confirm the provider's privacy policy for image storage/retention. If you cannot confirm api_base ownership or the publisher's identity, treat the skill as higher risk and avoid providing sensitive images or credentials.

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

OSWindows · Linux
Binscurl
Config[object Object]
latestvk978cqszq63xn3tt4da5f4m1sn83yk6e
185downloads
0stars
6versions
Updated 1w ago
v1.0.5
MIT-0
Windows, Linux

LC Scene Analysis HTTP

这是一个工地隐患分析模型技能,用于处理施工现场静态图片的安全隐患识别任务。

何时使用

当用户提供施工现场图片或图片 URL,并希望:

  • 识别图片中的安全隐患
  • 获取模型分析结果
  • 输出隐患结论或简要说明

此时使用本技能。

不要使用

以下情况不要调用本技能:

  • 视频流分析
  • 摄像头实时拉流
  • 本地模型推理
  • PLC、机器人、设备控制
  • 非施工现场图片分析
  • 与工地隐患识别无关的任务

前置要求

需要存在 auth profile:

  • lc_scene_http:default

该 profile 需提供以下字段:

  • api_base:服务基地址
  • api_key:接口认证信息
  • flow_id:默认 flowId
  • algorithm_id:默认 algorithmId,可为空

如果用户本次请求显式提供了 flow_idalgorithm_id,优先使用用户输入;否则使用默认配置。

不要向用户展示任何密钥、token、profile 内容或本地认证文件内容。

接口说明

1. 默认接口:智能巡检

接口:

POST /api/chat/agent/chatOnceNew

用途:

  • 默认图片隐患分析
  • 工地安全隐患识别
  • 普通分析请求优先走该接口

2. 数据采集接口

接口:

POST /api/chat/agent/chatOnceRaw

用途:

  • 用户明确要求数据采集
  • 用户明确要求结构化结果、原始结果、JSON 结果时调用

3. 交叉验证接口

接口:

POST /api/chat/agent/crossVerify

用途:

  • 用户明确要求交叉验证、复核、二次校验时调用
  • 当前会结合 CV 小模型对输出结果进行二次校验

选择规则

按以下规则选择接口:

  • 用户明确要求“交叉验证 / 复核 / 二次校验 / 再确认” → crossVerify
  • 用户明确要求“数据采集 / 原始结果 / 结构化结果 / JSON 结果” → chatOnceRaw
  • 其他普通工地隐患分析请求 → chatOnceNew

如果无法判断,默认使用 chatOnceNew

输入要求

优先接受以下输入:

  • 单张图片 URL
  • 多张图片 URL
  • 用户额外提供的 flow_id
  • 用户额外提供的 algorithm_id

如果没有图片或图片 URL,不要调用接口,应明确告知缺少输入。

请求要求

调用时:

  • lc_scene_http:default 读取默认配置
  • 使用其中的 api_baseapi_keyflow_idalgorithm_id
  • 若用户显式传入 flow_id / algorithm_id,则覆盖默认值
  • 默认调用 chatOnceNew
  • 仅在用户明确要求时调用 chatOnceRawcrossVerify

输出要求

  • 默认返回核心隐患识别结果
  • 如用户要求原始结果或结构化结果,尽量保留关键字段
  • 可以做简洁总结,但不要篡改关键结论
  • 不确定内容不要说成确定事实

错误处理

以下情况要明确报错,不要伪造结果:

  • auth profile 不存在
  • profile 缺少必要字段
  • 图片输入缺失
  • 服务返回 4xx / 5xx
  • 服务超时
  • 返回结构异常

安全要求

  • 不要输出密钥、token、Authorization 信息
  • 不要输出认证文件内容
  • 对外部图片 URL 保持谨慎
  • 如果任务明显超出工地隐患分析范围,不要强行调用本技能

示例

示例 1:默认分析

用户: “帮我分析这张施工现场图片有哪些隐患:https://example.com/a.jpg”

处理:

  • 调用 chatOnceNew

示例 2:数据采集

用户: “把这张图按结构化结果返回:https://example.com/b.jpg”

处理:

  • 调用 chatOnceRaw

示例 3:交叉验证

用户: “这张图再帮我做一次交叉验证:https://example.com/c.jpg”

处理:

  • 调用 crossVerify

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