Skills expert-finder

Name: expert-finder
Author: openclaw

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.

install

source · Clone the upstream repo

git clone https://github.com/openclaw/skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/atyachin/expert-finder" ~/.claude/skills/openclaw-skills-expert-finder && rm -rf "$T"

OpenClaw · Install into ~/.openclaw/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/atyachin/expert-finder" ~/.openclaw/skills/openclaw-skills-expert-finder && rm -rf "$T"

manifest: skills/atyachin/expert-finder/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="<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:

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