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Expert Finder
作者
Avital Yachin
· GitHub ↗
· v1.4.0
1328
总下载
2
收藏
1
当前安装
5
版本数
在 OpenClaw 中安装
/install expert-finder
功能描述
Find domain experts, thought leaders, and subject-matter authorities on any topic. Searches Twitter and Reddit for people who demonstrate deep knowledge, frequent discussion, and above-average expertise in a specific field. Expert discovery, talent sourcing, researcher identification, and KOL (Key Opinion Leader) mapping.
使用说明 (SKILL.md)
Expert Finder
Find domain experts by analyzing social media activity. Expands topics into search terms, searches Twitter/Reddit, classifies by type, and ranks.
Setup
Run xpoz-setup skill. Verify: mcporter call xpoz.checkAccessKeyStatus
4-Phase Process
Phase 1: Query Expansion
Research domain with web_search/web_fetch. Generate tiered queries:
| Tier | Purpose | Example (RLHF) |
|---|---|---|
| Tier 1: Core | Exact terms | "RLHF" |
| Tier 2: Technical | Deep jargon (strongest signal) | "reward model overfitting" |
| Tier 3: Adjacent | Related | "preference optimization" |
| Tier 4: Discussion | Opinion | "RLHF vs" |
Phase 2: Search & Aggregate
mcporter call xpoz.getTwitterPostsByKeywords query='"RLHF"' startDate="\x3C6mo>"
mcporter call xpoz.checkOperationStatus operationId="op_..." # Poll every 5s
Download CSVs via dataDumpExportOperationId (64K rows). Build author frequency: ≥3 posts, ≥2 tiers. Weight Tier 2 highest.
Phase 3: Classify & Score
Fetch profiles for top 20-30:
mcporter call xpoz.getTwitterUser identifier="user" identifierType="username"
Types: 🔬 Deep Expert (uses Tier 2 naturally) | 💡 Thought Leader (trends, large audience) | 🛠️ Practitioner ("I built") | 📣 Evangelist (aggregates) | 🎓 Educator (explains)
Score (0-100): Domain depth 30%, consistency 20%, peer recognition 20%, breadth 15%, credentials 15%.
Phase 4: Report
## Expert Report: [Domain] — X,XXX posts analyzed
#### 🥇 @username — 🔬 Deep Expert (92/100)
**Followers:** 12.4K | **Why:** 23 posts on reward optimization, advanced terminology
**Key:** "[quote]" — ❤️ 342
Tips
Narrow > broad | Tier 2 jargon = gold | Reddit comments reveal depth | 6mo window ideal
安全使用建议
This skill appears to be what it says: it uses an Xpoz client (mcporter) plus web search to discover experts. Before installing: 1) Verify the mcporter npm package (author, popularity, recent changes) and consider pinning a version; avoid installing unknown packages without review. 2) Inspect or run the xpoz-setup OAuth flow in a controlled way to see what permissions/tokens are granted and where tokens are stored. 3) Be aware that the skill will send queries and retrieved social media content to Xpoz (mcp.xpoz.ai), so review Xpoz's privacy policy if you care about sharing collected data. 4) If you want tighter control, restrict autonomous invocation or require explicit user approval before the skill runs network calls or installs packages. If you can provide the xpoz-setup code or the mcporter package URL/version, I can reassess with higher confidence.
功能分析
Type: OpenClaw Skill
Name: expert-finder
Version: 1.4.0
The skill is classified as suspicious due to its reliance on installing and executing an external `mcporter` binary via `npm`, which introduces a supply chain risk as `npm install` can execute arbitrary code. Additionally, the skill depends on a third-party network service (`mcp.xpoz.ai`) for its core functionality and utilizes powerful `web_search` and `web_fetch` tools. While the instructions in `SKILL.md` do not explicitly show malicious intent, these capabilities and external dependencies present a significant attack surface and potential for compromise if the external components are malicious.
能力评估
Purpose & Capability
The skill claims to find domain experts using Twitter/Reddit and the SKILL.md instructs the agent to call the Xpoz service via the mcporter CLI and to use web_search/web_fetch for query expansion. Requiring mcporter, the xpoz-setup helper, and network access to mcp.xpoz.ai is proportional to that purpose. Minor inconsistency: top-level registry metadata lists no explicit 'requires.skills' entry but SKILL.md metadata does require an 'xpoz-setup' skill and an Xpoz account (OAuth), which is plausible but should be noted.
Instruction Scope
Instructions are specific: expand queries, call mcporter to fetch posts and profiles, poll operation status, download CSVs, classify and produce a report. They do not instruct reading unrelated system files or environment variables, nor do they direct data to unexpected endpoints beyond Xpoz and web search tools. The skill will collect and process social media content (expected for the purpose).
Install Mechanism
The install spec is an npm package (mcporter) which is a traceable but moderate-risk mechanism (supply-chain risk). The package is not version-pinned in the spec, which increases risk. This is not an arbitrary URL download or archive extract, but you should verify the npm package identity, maintainer, and published version before installing.
Credentials
No environment variables are declared; authentication is delegated to the 'xpoz-setup' skill via OAuth 2.1, which is appropriate for a third-party service. The skill does require network access to mcp.xpoz.ai and will cause social-media data to be fetched and processed by Xpoz, which is consistent with the function but relevant to privacy and data-sharing considerations.
Persistence & Privilege
always:false and default autonomous invocation are normal. The skill depends on another setup skill to obtain credentials; that flow may persist tokens as part of normal OAuth behavior. Because the skill can run autonomously and call external services, consider the usual caution about granting network and install permissions, but there is no indication it requests elevated system privileges or modifies other skills.
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 expert-finder - 安装完成后，直接呼叫该 Skill 的名称或使用
/expert-finder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
v1.4.0
Added setup section
v1.3.0
Trimmed SKILL.md, added install spec
v1.2.0
Fix security scan: added prerequisites section documenting mcporter provenance, softened autonomous execution, removed references to unbundled scripts, improved CSV download instructions
v1.1.0
v1.1: Full CSV bulk analysis via datadump, Python/pandas code for author extraction at scale
v1.0.0
Find subject-matter experts, thought leaders, and practitioners on any topic via Twitter and Reddit analysis.
元数据
常见问题
Expert Finder 是什么？
Find domain experts, thought leaders, and subject-matter authorities on any topic. Searches Twitter and Reddit for people who demonstrate deep knowledge, frequent discussion, and above-average expertise in a specific field. Expert discovery, talent sourcing, researcher identification, and KOL (Key Opinion Leader) mapping. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 1328 次。
如何安装 Expert Finder？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install expert-finder」即可一键安装，无需额外配置。
Expert Finder 是免费的吗？
是的，Expert Finder 完全免费（开源免费），可自由下载、安装和使用。
Expert Finder 支持哪些平台？
Expert Finder 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 Expert Finder？
由 Avital Yachin（@atyachin）开发并维护，当前版本 v1.4.0。
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