← 返回 Skills 市场
413
总下载
1
收藏
0
当前安装
3
版本数
在 OpenClaw 中安装
/install mapping-skill
功能描述
AI/ML 人才搜索、论文作者发现、实验室成员爬取、GitHub 研究者挖掘与个性化招聘邮件生成 skill。只要用户提到查找 AI/ML PhD、研究员、工程师，抓取实验室成员、OpenReview/CVF 会议作者、GitHub 网络研究者，提取主页/Scholar/GitHub/邮箱/研究方向，识别华人、分...
安全使用建议
This skill contains full scraping scripts and explicit instructions to use OpenReview credentials, BrightData MCP tokens, and Feishu app_tokens to read and write user data, but the registry entry does not declare any required environment variables or permissions—this is a mismatch you should not ignore. Before installing or enabling it: 1) Require the author to declare exact env vars and scopes (OpenReview, BrightData, Feishu) and justify each; 2) Review and audit the scripts in a sandboxed environment (network-isolated VM) to confirm exactly what endpoints are called and what data is transmitted; 3) If you plan to connect Feishu or other production systems, use a limited-test account with minimal scopes and never reuse high-privilege tenant credentials; 4) Be aware the skill performs bulk email extraction and demographic ("华人") classification — verify legal/ethical compliance in your jurisdiction and organizational policy before using; 5) Prefer an explicit opt-in trigger (do not allow the skill to auto-run on vague matching intents) and require human approval before performing writes to external services. If the author cannot or will not clearly document required credentials and data flows, treat the skill as untrusted.
功能分析
Type: OpenClaw Skill
Name: mapping-skill
Version: 2.0.1
The Mapping-Skill bundle is a comprehensive toolkit for AI/ML talent recruitment, researcher data aggregation, and automated outreach. It contains specialized Python scripts (e.g., `openreview_scraper.py`, `cvf_paper_scraper.py`, `github_network_scraper.py`) for scraping academic conferences, laboratory homepages, and GitHub networks. The skill includes utilities for handling anti-scraping measures, such as `cloudflare_email_decoder.py`, and integrates with Feishu (Lark) for data management. All instructions in `SKILL.md` and the extensive documentation in the `references/` directory are strictly aligned with the stated purpose of talent sourcing and recruitment. While the skill requires network access and handles API credentials (GitHub, OpenReview, Serper), its behavior is transparent, well-documented, and lacks any indicators of malicious intent or unauthorized data exfiltration.
能力标签
能力评估
Purpose & Capability
The name/description (discover AI/ML researchers and generate outreach) matches the included scripts (openreview_scraper, cvf_paper_scraper, github_network_scraper, lab_member_scraper, cloudflare_email_decoder, serper_search, httpx_scraper). However the SKILL.md and README repeatedly instruct use of credentials and external services (OpenReview username/password, BrightData MCP token, Feishu app_token/table access) even though the registry metadata lists no required environment variables or credentials. Also the README/refs include many Feishu scopes and BrightData usage examples which are not reflected in requires.env—this mismatch is disproportionate and unexplained.
Instruction Scope
The SKILL.md instructs the agent to perform network scraping, decode Cloudflare-protected emails, extract and write CSV to /tmp, parse Feishu multi-dimensional table links to pull app_token/table_id, read and update Feishu records in bulk, and call BrightData MCP. It also instructs automatic triggering whenever user intent matches ("should be triggered even if user didn't explicitly say 'use Mapping-Skill'"). These instructions request access to sensitive data (personal emails, profiles) and sensitive actions (bulk writing to Feishu, generating outreach). They also direct the agent to use credentials that are not declared, and to perform ethnicity detection ("识别华人"), which is a sensitive classification. The instruction scope therefore goes beyond simple search tasks and requires clear, declared permissions and user consent.
Install Mechanism
There is no install specification in the registry (instruction-only), which is lower risk than arbitrary downloads. However the repository contains many Python scraper scripts and the README lists Python package dependencies (requests, BeautifulSoup, httpx, openreview-py, PyMuPDF, pandas, etc.). Those dependencies and any time-of-run network calls are not declared in the registry manifest. The absence of an install step means operators may run these scripts in an environment without expected sandboxing or dependency checks; this is a practical risk but not a direct sign of maliciousness.
Credentials
The skill declares no required environment variables or primary credential, yet the SKILL.md and README explicitly show code and examples that require: OpenReview username/password (OPENREVIEW_USER/OPENREVIEW_PASSWORD), BrightData MCP token (mcp URL token), and Feishu app_token / API credentials. The README also lists broad Feishu scopes. Requesting/using these credentials is proportionate for the described integrations only if they are explicitly declared and limited; the lack of declared env vars/config paths is an incoherence and increases the chance of accidental credential leaks or misuse. Additionally, the skill's built-in capability to identify '华人' (Chinese authors) is a sensitive demographic classification and requires careful justification and consent.
Persistence & Privilege
always:false and disable-model-invocation:false are standard. The SKILL.md's guidance that the skill 'should be prioritized' or 'should trigger even if user didn't explicitly request it' implies broad auto-invocation for matching intents; while autonomous invocation itself is normal, the combination with undisclosed credential needs and operations that modify external systems (Feishu batch updates) raises a surface-area concern. The skill does not request persistent 'always:true' privileges in the registry metadata.
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 mapping-skill - 安装完成后，直接呼叫该 Skill 的名称或使用
/mapping-skill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
v2.0.1
更新 Display name
v2.0.0
Mapping-Skill 2.0.0 is a major rewrite, focusing on expanding scenarios, best practices, and hands-on workflow clarity:
- Fully overhauled documentation, now in Chinese with detailed workflows for AI/ML talent mapping, paper author extraction, lab member scraping, and email generation.
- Added new reference docs: practice cases, prompt best practices, and user feedback notes for continuous improvement.
- Standardized steps for flying table (Feishu/飞书) import/export and batch personalized mail workflows.
- Emphasized selection of optimal data sources and anti-scraping strategies per scenario.
- Outlined role of each script and reference for reproducible, reliable results.
- Provided robust best-practice prompt patterns for OpenClaw, conference author extraction, and multi-table batch ops.
v1.0.0
- Initial release of AI Talent Recruiter (v1.0.0), an end-to-end workflow for discovering and reaching out to AI/ML talent.
- Supports candidate sourcing, profile scraping, deduplication, Chinese candidate identification, classification, and personalized email generation.
- Offers two scraping modes: BrightData MCP (paid, high success for LinkedIn/social) and Python scraping (free, for academic/personal pages).
- Includes detailed guides, reference templates, and ready-to-use scripts for each workflow stage.
- Provides robust deduplication, research field mapping (22 categories), and candidate classification tools.
元数据
常见问题
爬论文与人才触达工作流 是什么？
AI/ML 人才搜索、论文作者发现、实验室成员爬取、GitHub 研究者挖掘与个性化招聘邮件生成 skill。只要用户提到查找 AI/ML PhD、研究员、工程师，抓取实验室成员、OpenReview/CVF 会议作者、GitHub 网络研究者，提取主页/Scholar/GitHub/邮箱/研究方向，识别华人、分... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 413 次。
如何安装 爬论文与人才触达工作流？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install mapping-skill」即可一键安装，无需额外配置。
爬论文与人才触达工作流 是免费的吗？
是的，爬论文与人才触达工作流 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
爬论文与人才触达工作流 支持哪些平台？
爬论文与人才触达工作流 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 爬论文与人才触达工作流？
由 16Miku（@16miku）开发并维护，当前版本 v2.0.1。
推荐 Skills