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atyachin

Expert Finder

by Avital Yachin · GitHub ↗ · v1.4.0
cross-platform ⚠ suspicious
1328
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2
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1
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5
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Install in OpenClaw
/install expert-finder
Description
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.
README (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

Usage Guidance
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.
Capability Analysis
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.
Capability Assessment
✓ 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).
ℹ 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.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install expert-finder
  3. After installation, invoke the skill by name or use /expert-finder
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
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.
Metadata
Slug expert-finder
Version 1.4.0
License —
All-time Installs 1
Active Installs 1
Total Versions 5
Frequently Asked Questions

What is Expert Finder?

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. It is an AI Agent Skill for Claude Code / OpenClaw, with 1328 downloads so far.

How do I install Expert Finder?

Run "/install expert-finder" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Expert Finder free?

Yes, Expert Finder is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Expert Finder support?

Expert Finder is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Expert Finder?

It is built and maintained by Avital Yachin (@atyachin); the current version is v1.4.0.

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