alivirgo/major-ai-skills/verify-names-and-locations
Claude Code and agent skill by alivirgo/major-ai-skills
- community
Checking that the SKILL.md file is still in the repository.
Check names, titles, addresses, and locations against reliable sources before using them in a deliverable.
Install
npx vskill@latest install alivirgo/major-ai-skills/verify-names-and-locationsSKILL.md
Verify Names, Locations, & Entities (Entity Grounding) (AI Skill)
Overview
Large Language Models do not possess a live GPS or relational database of human beings; they generate names and locations based on statistical token probability.
When asked to generate market research ("Who is the Head of Procurement at Company X?" or "List 5 boutique coffee roasters in Austin, Texas"), AI models frequently synthesize plausible-sounding names, fake street addresses, and nonexistent executives.
The Entity Grounding Protocol establishes strict rules for detecting entity hallucinations and verifying proper nouns against external ground truth.
Statistical Plausibility vs. Ground-Truth Reality
The 4 High-Risk Entity Danger Zones
- Executive & Staff Names: Corporate turnover is rapid; models hallucinate past or fictional personnel.
- Physical Street Addresses & Suite Numbers: Models generate realistic-looking street numbers that lead to empty lots.
- Local Business Names & Phone Numbers: Phone numbers and store hours change frequently.
- Legal & Court Case Citations: Precedent case names (e.g. Smith v. Johnson Corp) are notoriously confabulated.
Master Entity Verification Prompt Templates
Pattern 1: The Named Entity Sourcing Directive
Use when conducting market intelligence, B2B lead generation, or competitive research:
Pattern 2: The Physical Location & Address Guardrail
Use for event planning, logistics, or real estate analysis:
Real-World Case Study
Scenario: Preparing a B2B Sales Outreach List
The AI Hallucination Failure
An SDR prompted AI: "List the VP of Security at 5 mid-market fintech companies."- The AI generated 5 names.- The SDR sent personalized cold emails.- 3 of the 5 people never worked at those companies; 1 had left 3 years prior.- Result: High bounce rate and damaged sender domain reputation.
The Entity Grounded Workflow
The SDR added the Grounding Rule: "List the companies and their current publicly stated Security hiring initiatives; provide LinkedIn search query links rather than generating specific personal names."- The SDR clicked the 5 verified LinkedIn search links in 60 seconds, identified the exact active VPs, and sent emails with 100% accuracy.
Summary Best Practices
- Never send an email to an AI-generated person's name without checking LinkedIn: Takes 10 seconds and prevents major embarrassment.
- Search address coordinates: Always paste addresses into Google Maps before booking travel or printing collateral.
Security
- Security scanPassed, 95 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/verify-names-and-locations/SKILL.md
Popularity
- Repository stars
- 1
- 7-day trend score
- 3
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
Works with
Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.
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