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多引擎全自动搜索聚合器
作者
chn012cjus
· GitHub ↗
· v1.0.3
· MIT-0
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在 OpenClaw 中安装
/install multi-engine-auto-search
功能描述
自动调用所有已安装搜索技能并行检索,去重交叉验证后整合排序,提供最全面、准确、实时的搜索结果。
安全使用建议
Before installing, consider these risks and mitigations:
- The aggregator will execute any 'search' skill found in your local skills directories with your user privileges. Audit the installed search skills first — a malicious or compromised skill can read files, network, and exfiltrate queries.
- The tool writes the query and reads results via shared TEMP files (mes_in.json / mes_result.json). Queries are stored in plaintext in the system temp directory and could be read by other local users/processes; child scripts may also write unexpected data. Prefer running in an isolated account or VM if queries are sensitive.
- The code contains inconsistent path assumptions (hardcoded Windows user path vs SKILL.md's ~/ paths) and an implicit dependency on curl.exe; it may fail or behave unexpectedly on non-Windows systems.
- Parallelism uses one worker per discovered skill; if you have many skills this may exhaust resources. The use of a single global temp filename introduces race conditions and possible tampering.
Recommendations: only install if you (a) inspect and trust the local search skills that will be invoked, (b) are comfortable with queries being written to the system temp directory, and (c) can run the aggregator in an isolated environment. If you plan to use it, modify the code to use per-process temp files (securely created), limit concurrency, and avoid hardcoded user paths or undocumented external binary requirements.
功能分析
Type: OpenClaw Skill
Name: multi-engine-auto-search
Version: 1.0.3
The skill contains hardcoded absolute Windows file paths to a specific user's directory (C:\Users\86195\...) in run.py, which is highly irregular for a portable skill and suggests it was extracted from a specific environment. It also implements a broad execution pattern that automatically runs any 'run.py' or 'search.py' file found in directories matching keywords like 'search' or 'browser', which could be leveraged for lateral code execution. While the logic aligns with its stated purpose as a search aggregator, the hardcoded environment-specific paths and the use of 'curl.exe' for direct Bing scraping (cn.bing.com) warrant caution.
能力评估
Purpose & Capability
The name/description (multi-engine aggregator) matches the code: it discovers search-related skills and invokes them to aggregate results. However SKILL.md refers to Unix-like ~/.openclaw paths while run.py uses hardcoded Windows paths (C:\Users\86195\.openclaw\...), which is an inconsistency. The code also depends on curl.exe for direct Bing fallback even though the registry metadata lists no external binary requirements.
Instruction Scope
The script scans local skill directories and launches each discovered skill as a subprocess, passing the user query and relying on a shared TEMP file (mes_result.json) for child-to-parent communication. This means the aggregator will execute arbitrary installed skill code with the agent user's privileges and will write/read plaintext query files in a shared temp location. The instructions/code also perform direct network requests (Bing via curl) as a fallback. These behaviors can expose sensitive queries to child scripts, other users/processes on the machine (via temp files), or external endpoints.
Install Mechanism
There is no install spec (instruction-only with bundled run.py). That minimizes supply-chain install risk; nothing is downloaded or extracted at install time. However the packaged run.py itself contains the execution logic, so the code shipped with the skill is what will run.
Credentials
The skill declares no required environment variables or credentials, which aligns with its local-aggregation purpose. It does, however, rely implicitly on the system TEMP directory (os.environ.get('TEMP')) and on the presence of curl.exe — neither of which are declared. The script also assumes the ability to read ~/.openclaw/skills (or the Windows equivalent) and execute scripts found there; that is expected for aggregating installed skills but grants broad local access.
Persistence & Privilege
The skill does not request always:true and is user-invocable only. It does spawn unbounded parallel workers in practice (ThreadPoolExecutor with max_workers=len(skills)), which could be large and cause resource exhaustion. It also uses a global temp file name for inter-process communication, creating possible race/symlink attacks or data leakage; but it does not attempt to modify other skills' configurations or request permanent platform privileges.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install multi-engine-auto-search - 安装完成后,直接呼叫该 Skill 的名称或使用
/multi-engine-auto-search触发 - 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
v1.0.3
Version 1.0.3 - Major logic and scope upgrade
- Now auto-discovers all installed search skills in specific directories and runs them in parallel, aggregating results.
- Adds mechanisms to deduplicate results by URL and handles no-result cases by automatic Bing fallback.
- Technical update: replaces fixed-engine curl script with ThreadPoolExecutor and subprocess calls to all detected search scripts.
- Improves robustness by communicating via temporary JSON file to solve encoding issues.
- Documentation updated to reflect broader auto-discovery logic, skill engine compatibility, and new output format.
v1.0.2
No changes detected in this version.
v1.0.1
multi-engine-auto-search v1.0.1
- 技能描述、功能说明和实际实现细节全面更新,反映仅支持 Bing,移除虚假“全引擎自动聚合”宣传。
- run.py 重构,直接通过 curl.exe 并行请求搜索引擎,移除对 OpenClaw tool call 的依赖。
- 文档说明实际只支持 Bing,详细列出技术细节与局限性。
- 增加修复记录,说明已更正过度宣传及实现偏差的问题。
v1.0.0
Auto-All-Search 1.0.0 introduces a fully automated, multi-engine search skill:
- Automatically detects and triggers searches across all installed search skills, requiring no user commands.
- Runs all search engines in parallel for faster, more comprehensive results.
- Merges, deduplicates, and cross-verifies results to maximize coverage and accuracy.
- Outputs include concise conclusions, source/tool breakdown, and prioritized result lists.
- Features automatic fallback to available engines if some fail, ensuring reliable search performance.
- Designed to completely replace single-tool search workflows.
元数据
常见问题
多引擎全自动搜索聚合器 是什么?
自动调用所有已安装搜索技能并行检索,去重交叉验证后整合排序,提供最全面、准确、实时的搜索结果。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 183 次。
如何安装 多引擎全自动搜索聚合器?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install multi-engine-auto-search」即可一键安装,无需额外配置。
多引擎全自动搜索聚合器 是免费的吗?
是的,多引擎全自动搜索聚合器 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
多引擎全自动搜索聚合器 支持哪些平台?
多引擎全自动搜索聚合器 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 多引擎全自动搜索聚合器?
由 chn012cjus(@chn012cjus)开发并维护,当前版本 v1.0.3。
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