Expert Finder
by @atyachin
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.
clawhub install expert-finderπ About This Skill
name: 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." homepage: https://xpoz.ai metadata: { "openclaw": { "requires": { "bins": ["mcporter"], "skills": ["xpoz-setup"], "tools": ["web_search", "web_fetch"], "network": ["mcp.xpoz.ai"], "credentials": "Xpoz account (free tier) β auth via xpoz-setup skill (OAuth 2.1)", }, "install": [{"id": "node", "kind": "node", "package": "mcporter", "bins": ["mcporter"], "label": "Install mcporter (npm)"}], }, } tags: - expert-finder - domain-expert - thought-leader - talent-sourcing - researcher - KOL - twitter - reddit - social-media - knowledge - authority - subject-matter-expert - people-search - intelligence - mcp - xpoz
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: β₯3 posts, β₯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: π¬ Deep Expert (uses Tier 2 naturally) | π‘ Thought Leader (trends, large audience) | π οΈ Practitioner ("I built") | π£ Evangelist (aggregates) | π Educator (explains)
Score (0-100): Domain depth 30%, consistency 20%, peer recognition 20%, breadth 15%, credentials 15%.
Phase 4: Report
## Expert Report: [Domain] β X,XXX posts analyzed#### π₯ @username β π¬ Deep Expert (92/100)
Followers: 12.4K | Why: 23 posts on reward optimization, advanced terminology
Key: "[quote]" β β€οΈ 342
Tips
Narrow > broad | Tier 2 jargon = gold | Reddit comments reveal depth | 6mo window ideal
βοΈ Configuration
Run xpoz-setup skill. Verify: mcporter call xpoz.checkAccessKeyStatus
π Tips & Best Practices
Narrow > broad | Tier 2 jargon = gold | Reddit comments reveal depth | 6mo window ideal