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Expert Finder

Find domain experts, thought leaders, and subject-matter authorities on any topic.

Rating: 4.7 (264 reviews)
Downloads: 540 downloads
Version: 1.0.0

Overview

Find domain experts, thought leaders, and subject-matter authorities on any topic.

Complete Documentation

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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

bash

mcporter call xpoz.getTwitterPostsByKeywords query='"RLHF"' startDate="<6mo>"
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:

bash

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

markdown

## 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

Installation

Terminal bash


openclaw install expert-finder

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💻Code Examples

mcporter call xpoz.checkOperationStatus operationId="op_..." # Poll every 5s

mcporter-call-xpozcheckoperationstatus-operationidop--poll-every-5s.txt

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"

mcporter-call-xpozgettwitteruser-identifieruser-identifiertypeusername.txt

**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

example.md

## 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