Apollo Lead Finder
gooseworks-ai/goose-skills
Two-phase Apollo.io prospecting: free People Search to discover ICP-matching leads, then selective enrichment to reveal emails/phones (credits per contact).
AI原生的潜在客户情报与外联管道。取代Apollo、Clay和ZoomInfo，提供基于代理的信号评分、相互排名、温暖路径发现、来源驱动的语音建模以及跨电子邮件、LinkedIn和X的渠道特定外联。当用户想要查找、筛选并联系高价值联系人时使用。
Install Lead Intelligence
$ npx skills add affaan-m/ECC --skill lead-intelligence -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install affaan-m/ECC lead-intelligence --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/docs/zh-CN/skills/lead-intelligence .claude/skills/lead-intelligence && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "lead-intelligence" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/zh-CN/skills/lead-intelligence into .claude/skills/lead-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lead-intelligence", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/affaan-m/ECC/tree/main/docs/zh-CN/skills/lead-intelligenceType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add affaan-m/ECC --skill lead-intelligence -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install affaan-m/ECC lead-intelligence --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .agents/skills && cp -r skills-src/docs/zh-CN/skills/lead-intelligence .agents/skills/lead-intelligence && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "lead-intelligence" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/zh-CN/skills/lead-intelligence into .agents/skills/lead-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lead-intelligence", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add affaan-m/ECC --skill lead-intelligence -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install affaan-m/ECC lead-intelligence --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/docs/zh-CN/skills/lead-intelligence .cursor/skills/lead-intelligence && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "lead-intelligence" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/zh-CN/skills/lead-intelligence into .cursor/skills/lead-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lead-intelligence", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/affaan-m/ECC.git --path docs/zh-CN/skills/lead-intelligence--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add affaan-m/ECC --skill lead-intelligence -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install affaan-m/ECC lead-intelligence --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/docs/zh-CN/skills/lead-intelligence .gemini/skills/lead-intelligence && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "lead-intelligence" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/zh-CN/skills/lead-intelligence into .gemini/skills/lead-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lead-intelligence", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install affaan-m/ECC lead-intelligenceInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add affaan-m/ECC --skill lead-intelligence -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .github/skills && cp -r skills-src/docs/zh-CN/skills/lead-intelligence .github/skills/lead-intelligence && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "lead-intelligence" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/zh-CN/skills/lead-intelligence into .github/skills/lead-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lead-intelligence", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add affaan-m/ECC --skill lead-intelligence -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install affaan-m/ECC lead-intelligence --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/affaan-m/ECC.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/docs/zh-CN/skills/lead-intelligence .opencode/skills/lead-intelligence && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "lead-intelligence" agent skill from https://github.com/affaan-m/ECC/tree/main/docs/zh-CN/skills/lead-intelligence into .opencode/skills/lead-intelligence/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lead-intelligence", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
lead-intelligence- GitHub stars
- 275k
- Token cost
- ~1.5k tokens
- SKILL.md length
- 267 words
- Files
- 1
- Skills in repo
- 645
- Repo updated
- First seen
- Licence
- MIT
At a glance
AI原生的潜在客户情报与外联管道。取代Apollo、Clay和ZoomInfo，提供基于代理的信号评分、相互排名、温暖路径发现、来源驱动的语音建模以及跨电子邮件、LinkedIn和X的渠道特定外联。当用户想要查找、筛选并联系高价值联系人时使用。
- Works in 4 steps: 拉取用户的X关注列表和LinkedIn联系人 → 对于每个高信号目标，检查共享联系人 → 应用 social-graph-ranker 模型来评分桥梁价值 → …
- Tasks that involve GraphQL
- SKILL.md covers 何时激活, 工具要求, 管道概览 and 外联前的语气, plus 9 more sections
- Needs X_BEARER_TOKEN and X_CONSUMER_KEY
What it does
Lead Intelligence is an agent skill from affaan-m/ECC. AI原生的潜在客户情报与外联管道。取代Apollo、Clay和ZoomInfo，提供基于代理的信号评分、相互排名、温暖路径发现、来源驱动的语音建模以及跨电子邮件、LinkedIn和X的渠道特定外联。当用户想要查找、筛选并联系高价值联系人时使用。
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Backend & APIs, covering GraphQL. It works with LinkedIn. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.
When your agent uses it
- Tasks that involve GraphQL
Example prompts
- “/lead-intelligence”
Requirements
- Python 3
- A credential in X_BEARER_TOKEN
- A credential in X_CONSUMER_KEY
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- 拉取用户的X关注列表和LinkedIn联系人
- 对于每个高信号目标，检查共享联系人
- 应用 social-graph-ranker 模型来评分桥梁价值
- 根据以下因素对共同联系人进行排名
What it can do on your machine
Read from SKILL.md and the folder at commit ef648e0. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are python and bash).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
X_BEARER_TOKENX_CONSUMER_KEYX_CONSUMER_SECRETX_ACCESS_TOKENX_ACCESS_TOKEN_SECRETEXA_API_KEYAPOLLO_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Lead Intelligence loads about 1.5k tokens when it runs. Until then it costs about 35 tokens; SKILL.md has 267 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from affaan-m/ECC at commit ef648e0, republished under its MIT licence (© affaan-m). 267 words, ~1,494 tokens.
Download SKILL.mdSave it as
.claude/skills/lead-intelligence/SKILL.md (or your agent's skills folder).- name
- lead-intelligence
- description
- AI原生的潜在客户情报与外联管道。取代Apollo、Clay和ZoomInfo，提供基于代理的信号评分、相互排名、温暖路径发现、来源驱动的语音建模以及跨电子邮件、LinkedIn和X的渠道特定外联。当用户想要查找、筛选并联系高价值联系人时使用。
- origin
- ECC
线索情报
基于智能体的线索情报管道，通过社交图谱分析与温暖路径发现，寻找、评分并触达高价值联系人。
何时激活
- 用户希望在特定行业寻找线索或潜在客户
- 为合作、销售或融资构建外联名单
- 研究应该联系谁以及最佳联系路径
- 用户提及"寻找线索"、"外联名单"、"我应该联系谁"、"温暖引荐"
- 需要根据相关性对联系人列表进行评分或排序
- 希望绘制共同联系人图谱以寻找温暖引荐路径
工具要求
必需
- Exa MCP — 用于人员、公司和信号的深度网络搜索（
web_search_exa） - X API — 关注者/关注图谱、共同联系人分析、近期活动（
X_BEARER_TOKEN，以及写上下文凭据，如X_CONSUMER_KEY、X_CONSUMER_SECRET、X_ACCESS_TOKEN、X_ACCESS_TOKEN_SECRET）
可选（增强结果）
- LinkedIn — 如果可用则使用直接API，否则使用浏览器控制进行搜索、资料查看和消息草拟
- Apollo/Clay API — 如果用户有访问权限，用于丰富化交叉引用
- GitHub MCP — 用于以开发者为中心的线索资格评估
- Apple Mail / Mail.app — 草拟冷邮件或温暖邮件，但不自动发送
- 浏览器控制 — 当API覆盖不足或受限时，用于LinkedIn和X
管道概览
┌─────────────┐ ┌──────────────┐ ┌─────────────────┐ ┌──────────────┐ ┌─────────────────┐
│ 1. 信号评分 │────>│ 2. 相互排序 │────>│ 3. 发现热路径 │────>│ 4. 丰富内容 │────>│ 5. 起草外联 │
└─────────────┘ └──────────────┘ └─────────────────┘ └──────────────┘ └─────────────────┘外联前的语气
不要从通用的销售文案中起草外联信息。
当用户的语气很重要时，首先运行 brand-voice。在此技能中重复使用其 VOICE PROFILE，而不是临时重新推导风格。
如果实时X访问可用，在起草前拉取最近的原创帖子。如果不可用，则使用提供的示例或最佳的仓库/网站材料。
阶段 1：信号评分
在目标垂直领域中搜索高信号人员。根据以下标准为每个人分配权重：
| 信号 | 权重 | 来源 |
|---|---|---|
| 角色/职位匹配 | 30% | Exa, LinkedIn |
| 行业匹配 | 25% | Exa 公司搜索 |
| 近期相关话题活动 | 20% | X API 搜索, Exa |
| 关注者数量/影响力 | 10% | X API |
| 地理位置接近度 | 10% | Exa, LinkedIn |
| 与您内容的互动 | 5% | X API 互动 |
信号搜索方法
# Step 1: Define target parameters
target_verticals = ["prediction markets", "AI tooling", "developer tools"]
target_roles = ["founder", "CEO", "CTO", "VP Engineering", "investor", "partner"]
target_locations = ["San Francisco", "New York", "London", "remote"]
# Step 2: Exa deep search for people
for vertical in target_verticals:
results = web_search_exa(
query=f"{vertical} {role} founder CEO",
category="company",
numResults=20
)
# Score each result
# Step 3: X API search for active voices
x_search = search_recent_tweets(
query="prediction markets OR AI tooling OR developer tools",
max_results=100
)
# Extract and score unique authors阶段 2：共同联系人排名
对于每个评分目标，分析用户的社交图谱以找到最温暖的路径。
排名模型
- 拉取用户的X关注列表和LinkedIn联系人
- 对于每个高信号目标，检查共享联系人
- 应用
social-graph-ranker模型来评分桥梁价值 - 根据以下因素对共同联系人进行排名：
| 因素 | 权重 |
|---|---|
| 与目标的联系数量 | 40% — 最高权重，联系最多 = 排名最高 |
| 共同联系人的当前角色/公司 | 20% — 决策者 vs 个人贡献者 |
| 共同联系人的地理位置 | 15% — 同一城市 = 更容易引荐 |
| 行业匹配 | 15% — 同一垂直领域 = 自然引荐 |
| 共同联系人的X账号/LinkedIn | 10% — 可识别性以便外联 |
规范规则：
当用户需要图数学本身、作为独立报告的桥接排名或显式衰减模型调优时，使用 social-graph-ranker。在此技能中，使用相同的加权桥梁模型：
B(m) = Σ_{t ∈ T} w(t) · λ^(d(m,t) - 1)
R(m) = B_ext(m) · (1 + β · engagement(m))解读：
- 第1层：高
R(m)和直接桥梁路径 -> 请求温暖引荐 - 第2层：中等
R(m)和一跳桥梁路径 -> 有条件地请求引荐 - 第3层：无可行桥梁 -> 使用相同的线索记录进行直接冷外联
输出格式
如果用户明确要求将排名引擎单独拆分、将数学计算可视化，或在完整线索工作流之外对网络进行评分，请先独立运行 `social-graph-ranker` 作为独立步骤，然后将结果反馈回此流程。
相互排名报告
=====================
#1 @mutual_handle (得分: 92)
姓名: Jane Smith
角色: Partner @ Acme Ventures
地点: San Francisco
与目标对象的连接数: 7
关联对象: @target1, @target2, @target3, @target4, @target5, @target6, @target7
最佳引荐路径: Jane 投资了 Target1 的公司
#2 @mutual_handle2 (得分: 85)
...阶段 3：温暖路径发现
对于每个目标，找到最短的引荐链：
你 ──[关注]──> 互关A ──[投资了]──> 目标公司
你 ──[关注]──> 互关B ──[共同创立了]──> 目标人物
你 ──[在]──> 活动 ──[也参加了]──> 目标人物路径类型（按温暖度排序）
- 直接共同联系人 — 你们都关注/认识同一个人
- 投资组合联系 — 共同联系人投资或担任目标公司顾问
- 同事/校友 — 共同联系人在同一家公司工作或就读同一所学校
- 活动重叠 — 双方都参加了同一会议/项目
- 内容互动 — 目标与共同联系人的内容互动，反之亦然
阶段 4：丰富化
对于每个合格的线索，拉取：
- 全名、当前职位、公司
- 公司规模、融资阶段、近期新闻
- 近期X帖子（最近30天）— 主题、语气、兴趣
- 与用户的共同兴趣（共享关注、相似内容）
- 近期公司事件（产品发布、融资轮次、招聘）
丰富化来源
- Exa：公司数据、新闻、博客文章
- X API：近期推文、简介、关注者
- GitHub：开源贡献（针对以开发者为中心的线索）
- LinkedIn（通过浏览器使用）：完整资料、经历、教育背景
阶段 5：外联草稿
为每个线索生成个性化的外联信息。草稿应与来源匹配的语气配置文件和目标渠道保持一致。
渠道规则
电子邮件
- 用于最高价值的冷外联、温暖引荐、投资者外联和合作请求
- 当本地桌面控制可用时，默认在 Apple Mail / Mail.app 中起草
- 首先创建草稿，除非用户明确要求，否则不要自动发送
- 主题行应简洁具体，不要耍小聪明
- 当目标在LinkedIn上活跃、共同图谱上下文在LinkedIn上更强或电子邮件信心不足时使用
- 如果可用，优先使用API访问
- 否则使用浏览器控制查看资料、近期活动和起草消息
- 保持比电子邮件更短，避免虚假的职业热情
X
- 用于高上下文的操作者、建设者或投资者外联，其中公开发帖行为很重要
- 优先使用API访问进行搜索、时间线和互动分析
- 必要时回退到浏览器控制
- 私信和公开回复应比电子邮件更紧凑，并引用目标时间线上真实的内容
渠道选择启发式
按以下顺序选择一个主要渠道：
- 通过电子邮件进行温暖引荐
- 直接电子邮件
- LinkedIn 私信
- X 私信或回复
仅在有充分理由且节奏不会显得像垃圾邮件时使用多渠道。
温暖引荐请求（给共同联系人）
目标：
- 一个明确的请求
- 一个具体的理由说明为什么这次引荐有意义
- 如果需要，提供易于转发的简介
避免：
- 过度解释您的公司
- 堆叠社会证明
- 听起来像筹款模板
直接冷外联（给目标）
目标：
- 从具体且近期的事情开始
- 解释为什么契合度是真实的
- 提出一个低摩擦的请求
避免：
- 泛泛的赞美
- 功能倾倒
- 宽泛的请求，如"很乐意联系"
- 强加的反问句
执行模式
对于每个目标，生成：
- 推荐的渠道
- 该渠道最佳的理由
- 消息草稿
- 可选的跟进草稿
- 如果电子邮件是选定的渠道且 Apple Mail 可用，则创建草稿而不仅仅是返回文本
如果浏览器控制可用：
- LinkedIn：查看目标资料、近期活动和共同联系人上下文，然后起草或准备消息
- X：查看近期帖子或回复，然后起草私信或公开回复语言
如果桌面自动化可用：
- Apple Mail：创建包含主题、正文和收件人的草稿电子邮件
未经用户明确批准，不要自动发送消息。
反模式
- 没有个性化的通用模板
- 解释整个公司的长段落
- 一条消息中包含多个请求
- 没有具体细节的虚假熟悉感
- 带有可见合并字段的批量发送消息
- 为电子邮件、LinkedIn 和 X 重复使用相同的副本
- 平台化的废话，而不是作者的真实语气
配置
用户应设置以下环境变量：
# Required
export X_BEARER_TOKEN="..."
export X_ACCESS_TOKEN="..."
export X_ACCESS_TOKEN_SECRET="..."
export X_CONSUMER_KEY="..."
export X_CONSUMER_SECRET="..."
export EXA_API_KEY="..."
# Optional
export LINKEDIN_COOKIE="..." # For browser-use LinkedIn access
export APOLLO_API_KEY="..." # For Apollo enrichment智能体
此技能在 agents/ 子目录中包含专门的智能体：
- signal-scorer — 根据相关性信号搜索和排名潜在客户
- mutual-mapper — 映射社交图谱连接并寻找温暖路径
- enrichment-agent — 拉取详细的个人资料和公司数据
- outreach-drafter — 生成个性化消息
使用示例
用户：帮我找出预测市场中我应该联系的20位顶尖人物
智能体工作流程：
1. signal-scorer 在 Exa 和 X 上搜索预测市场领导者
2. mutual-mapper 检查用户的 X 社交图谱以寻找共同联系人
3. enrichment-agent 提取公司数据和近期动态
4. outreach-drafter 为排名靠前的潜在联系人生成个性化消息
输出：包含热路径、语音画像摘要以及针对特定渠道或应用内草稿的排名列表相关技能
brand-voice用于规范语气捕获connections-optimizer用于在外联前进行先审后用的网络修剪和扩展
© affaan-m, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in docs/zh-CN/skills/lead-intelligence of affaan-m/ECC.
Open the folder on GitHubat commit ef648e0
Compare with similar skills
Lead Intelligence next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Lead Intelligence this skillaffaan-m/ECC | 275k | — | ~1.5k | Automated safety check: Pass | MIT | |
| Apollo Lead Findergooseworks-ai/goose-skills | 1.2k | 1 repos | ~2k | Automated safety check: Notes | MIT | |
| Lead IntelligenceaAAaqwq/AGI-Super-Team | 105 | 3 repos | ~2.8k | Automated safety check: Pass | MIT | |
| Leadership Change Outreachgooseworks-ai/goose-skills | 1.2k | 1 repos | ~7.9k | Automated safety check: Pass | MIT | |
| Company Contact Findermajiayu000/claude-skill-registry | 666 | 2 repos | ~2.7k | Automated safety check: Pass | MIT | |
| API DesignerJeffallan/claude-skills | 12k | 2 repos | ~2k | Automated safety check: Pass | MIT |
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Related
Works with
Categories
Questions about Lead Intelligence
What does Lead Intelligence do?
AI原生的潜在客户情报与外联管道。取代Apollo、Clay和ZoomInfo，提供基于代理的信号评分、相互排名、温暖路径发现、来源驱动的语音建模以及跨电子邮件、LinkedIn和X的渠道特定外联。当用户想要查找、筛选并联系高价值联系人时使用。. Lead Intelligence is an agent skill from affaan-m/ECC.
When should I use Lead Intelligence?
Lead Intelligence fits situations like: tasks that involve GraphQL.
How do I install Lead Intelligence in Claude Code?
Run `npx skills add affaan-m/ECC --skill lead-intelligence -a claude-code`. Or copy the skill folder (docs/zh-CN/skills/lead-intelligence in affaan-m/ECC) into .claude/skills/lead-intelligence in your project. Claude Code loads it when a task matches its description.
How do I install Lead Intelligence in Codex?
Run `npx skills add affaan-m/ECC --skill lead-intelligence -a codex`. Or copy the skill folder (docs/zh-CN/skills/lead-intelligence in affaan-m/ECC) into .agents/skills/lead-intelligence in your project. Codex loads it when a task matches its description.
Can I use Lead Intelligence in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add affaan-m/ECC --skill lead-intelligence -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/lead-intelligence, .gemini/skills/lead-intelligence, .github/skills/lead-intelligence and .opencode/skills/lead-intelligence in your project.
What does Lead Intelligence need to run?
Going by SKILL.md and its folder, Lead Intelligence needs credentials named X_BEARER_TOKEN, X_CONSUMER_KEY, X_CONSUMER_SECRET and X_ACCESS_TOKEN. Our summary lists: Python 3; A credential in X_BEARER_TOKEN; A credential in X_CONSUMER_KEY.
Does Lead Intelligence access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Lead Intelligence safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Lead Intelligence use?
Lead Intelligence is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Lead Intelligence use?
About 1.5k tokens (SKILL.md is roughly 6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Lead Intelligence?
Skills that share tags, products or a category with Lead Intelligence: Apollo Lead Finder (gooseworks-ai/goose-skills, 1.2k stars), Lead Intelligence (aAAaqwq/AGI-Super-Team, 105 stars), Leadership Change Outreach (gooseworks-ai/goose-skills, 1.2k stars) and Company Contact Finder (majiayu000/claude-skill-registry, 666 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Lead Intelligence?
affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 275,023 GitHub stars. The repository holds 645 skills in this directory. The repository was last updated on October 5, 2026.
Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.