论文安装
- 作者仓库星标 0
- 作者更新于 实时读取
- 作者仓库 nano-core
- 领域
- 数据
- 兼容 Agent
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- 信任分
- 88 / 100 · 社区维护
- 作者 / 版本 / 许可
- @0-CYBERDYNE-SYSTEMS-0 · 未声明 license
- Token 消耗评级
- 低消耗
- 接入复杂程度
- 即装即用
- 是否需要外部 API Key
- 不需要
- 兼容的系统
- 未声明(默认跨平台)
- 底层运行要求
- Python
- 文件与系统权限
-
- 只读
- 允许写入 / 修改
- 网络行为
- 仅限本地
- 安装命令数
- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: business-contact-recon
description: Free OSINT reconnaissance to discover, validate, and build outreach-ready contact lists for busi…
category: 数据
runtime: Python
---
# business-contact-recon 输出预览
## PART A: 任务判断
- 适用问题:表格、CSV、数据集、指标或分析流程。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“When not to use this skill / When to Use / Prerequisites”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于表格、CSV、数据集、指标或分析流程,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“When not to use this skill / When to Use / Prerequisites”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、写入/修改文件、主要在本地完成、通常不需要额外 API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件;主要在本地完成;通常不需要额外 API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 先确认触发方式
原文没有稳定的斜杠命令要求。安装验证后通常全局生效,直接在对话里点名这个 Skill 并描述任务即可。
给清楚输入和边界
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、写入/修改文件。
小样例验证后再放大
先用一个小任务确认它会围绕“When not to use this skill / When to Use / Prerequisites”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
复核后再交付
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: business-contact-recon
description: Free OSINT reconnaissance to discover, validate, and build outreach-ready contact lists for busi…
category: 数据
source: 0-CYBERDYNE-SYSTEMS-0/nano-core
---
# business-contact-recon
## 什么时候使用
- business-contact-recon 是数据方向的技能,让 Agent 处理结构化文件(Excel / CSV / 表格) 适合处理表格、CSV、指标、数据集、分析和可视化报告,核心价值是把输入、判断、执行、验证和交付边界固定下…
- 面向表格、CSV、数据集、指标或分析流程,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「When not to use this skill / When to Use / Prerequisites」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件;主要在本地完成;通常不需要额外 API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 证据边界与执行链路
作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "business-contact-recon" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> When not to use this skill / When to Use / Prerequisites
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> Python | 读取文件、写入/修改文件 | 主要在本地完成
安全层 -> 通常不需要额外 API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} Business Contact Reconnaissance Skill
When not to use this skill
- Do not use when another skill is a better direct match for the task.
- Do not use when the request is outside this skill's scope.
When to Use
Build targeted outreach lists using free public data sources:
- Sales lead generation by region/industry
- Business validation before contact attempts
- Discovering key personnel (owners, managers, decision-makers)
- Regional/niche market research
Prerequisites
# Core dependencies
pip install requests beautifulsoup4 lxml python-dateutil
# Optional (for advanced extraction)
pip install linkedin-api # Free tier with limitations
No paid APIs required. All sources in this skill are free.
Core Workflow
Phase 1: Discovery
- Define target parameters (region, keywords, industry)
- Run web searches to discover businesses
- Filter by location/relevance
- Compile seed list
Phase 2: Validation
Cross-reference each business:
- Social presence (LinkedIn, website, social links)
- Review activity (Google, Yelp)
- Recent mentions (news, blogs)
- Government records (state biz registries)
- Forum/community signals
Phase 3: Contact Extraction
For validated businesses:
- Scrape website contact pages (respect robots.txt)
- Find LinkedIn company page → extract key personnel
- Use pattern-based email guessing (first@business.com)
Phase 4: Output
Generate CSV with standardized fields.
Available Scripts
| Script | Purpose |
|---|---|
scripts/discover_businesses.py |
DuckDuckGo + web discovery |
scripts/validate_activity.py |
Multi-signal validation |
scripts/extract_contacts.py |
Contact extraction from websites |
scripts/linkedin_extract.py |
Free LinkedIn company/person data |
scripts/build_csv.py |
Generate CRM-ready CSV |
Free Data Sources Priority
- Search engines: DuckDuckGo (no tracking, no API limits)
- Business listings: Google Maps, Yelp (public pages)
- Social: LinkedIn (public profiles only, no scraping)
- Government: State Secretary of State business databases
- Domains: WHOIS lookup, website analysis
- News: RSS feeds, Google News alerts
Compliance & Safety
✅ Allowed (Free Tier)
- Public business listings and directories
- Website contact pages (respect rate limits)
- LinkedIn public profiles
- Government records (public domain)
- DuckDuckGo/Google search results
⚠️ Use Caution
- Website scraping: 1 req/sec max, respect robots.txt
- Email pattern guessing: verify before sending
- LinkedIn: no automation tools, manual data only
❌ Never Do
- Credential stuffing or account takeover
- Bypassing CAPTCHAs or rate limits
- Scraping behind login walls
- Harvesting personal phone numbers
- Using paid APIs you don't have keys for
Output Format
business_name,website,phone,email,contact_name,title,linkedin_url,source,confidence,last_verified,notes
Joe's Plumbing,https://joesplumbing.com,555-0123,joe@joesplumbing.com,Joe Smith,Owner,,website+hunter,high,2026-02-06,"Local SEO present"
Rate Limiting
- Search engines: 1 query per 3 seconds (DuckDuckGo is lenient)
- Websites: 1 request per second
- LinkedIn: Manual extraction only (no API/scripted access)
- General: Be respectful, don't impact target sites
Reference Documentation
- Free Data Sources - Detailed guide to all free APIs and databases
- Industry Templates - Pre-built search patterns by industry
- Compliance Guidelines - Do's and don'ts for ethical OSINT
- CSV Schema - Field definitions and validation rules
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核