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shengwang-integration胜网集成

Agent Skill

shengwang-integration 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

353

周安装

15

GitHub Stars

公开资料未说明

下载量

124
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:shengwang-integration(胜网集成)
来源仓库:https://github.com/hugochaan/agent-skills
仓库路径:skills/shengwang-integration
安装命令:
npx skills add https://github.com/hugochaan/agent-skills --skill shengwang-integration
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/hugochaan/agent-skills --skill shengwang-integration

简介

用于查找、检索和筛选相关信息,支持关键词匹配和线索定位。

  • 适合在开发中快速获取候选方案或技术资料。shengwang-integration 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 可结合来源仓库和 README 进一步核验具体实现方式。
  • 安装前应确认是否会触发联网、命令执行或文件读写操作。
  • 注意权限范围和仓库维护状态,避免误用或安全风险。

SKILL.md

Shengwang Integration

Workflow

Step 0: Ensure doc index exists (MANDATORY)

⚠️ This step is NON-NEGOTIABLE. Execute it BEFORE any routing, intake, or code generation.

Check if references/docs.txt exists. If not (or if this is a fresh project), download it immediately:

bash skills/shengwang-integration/scripts/fetch-docs.sh

This file is the documentation index — all doc lookups depend on it. Do NOT proceed to Step 1 until this file exists or the download has been attempted. If download fails, proceed with local reference docs and fallback URLs.

Step 1: Collect kickoff information

Use intake to collect kickoff information. Ask only for details the user has not already provided.

Collect only the details needed to remove implementation blockers:

  • User's use case / target solution
  • Main Shengwang / Agora product
  • Platform or client stack
  • Backend language if relevant
  • Any key technical details already known that affect routing or implementation

Use a conversational flow:

  • Ask one short question at a time
  • Infer obvious context from the user's request when it is safe to do so
  • Ask only for the next most useful missing detail
  • Stop asking as soon as there is enough information to continue

For product-specific preferences such as ConvoAI vendors, do not force a full configuration upfront. Use recommended defaults as short suggestions, but for ConvoAI the user must still explicitly answer or confirm all of these fields before implementation:

  • ASR
  • ASR language
  • LLM
  • TTS

"Use the default" is a valid explicit confirmation. Collect these confirmations one at a time, not as a large form.

If the user already gave enough information, do not repeat questions. Produce a lightweight kickoff recap, then continue automatically unless a required detail is still missing.

Step 2: Start with local references

Use the kickoff summary plus the route table below to select the correct local reference module. If the available information is sufficient, begin implementation using the existing local docs under references/.

PurposeRoute to
New request, vague, or missing detailsintake
Credentials, AppID, REST authgeneral
Download SDK, sample project, Token Builder, GitHub repoRoute to the relevant product module
Generate Token, token server, AccessToken2, RTC/RTM authtoken-server
ConvoAI operation (with details already known)conversational-ai
RTC SDK integrationrtc
RTM messaging / signalingrtm
Cloud Recordingcloud-recording

If Step 2 provides enough information for implementation, proceed. If essential information is still missing or the local references are not enough, continue to Step 3.

Step 3: Research with doc fetching

Use references/doc-fetching.md to fetch more comprehensive documentation. Do this only after Step 2, when the local references are insufficient for the requested implementation.

Research order:

  1. Local references in this skill
  2. Fetched docs via the doc-fetching workflow
  3. Fallback web search only if needed after doc fetching

Once Step 3 provides enough information, proceed with implementation.

Download Rules

  • Use git clone --depth 1 <url> — GitHub URLs must be repo root only (no branch/subdirectory paths)
  • On any download failure: report the error, provide the URL for manual download, never silently skip

Links

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

33.24%
按下载量换算41

Claude

31.86%
按下载量换算40

Cursor

20.92%
按下载量换算26

Gemini CLI

10.11%
按下载量换算13

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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