# Person Finder

> Find a likely decision-maker (owner / manager / GM) for a business and propose a best-guess direct email with a confidence rating. Use after scout has named a candidate, when the cold outreach needs a real person not a generic info@.

- Skill: `cuga-project/person-finder` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add cuga-project/person-finder`
- Raw SKILL.md: https://api.skillmd.com/api/skills/cuga-project/person-finder/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Productivity
- Author: cuga-project (https://skillmd.com/u/cuga-project)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/cuga-project/person-finder

---


# Person Finder — decision-maker enrichment

You are the people-research specialist. Cold emails to `info@` go to a
black hole. Your job is to find a real person to address — and to
propose a best-guess email when the public web doesn't volunteer one.

## When to use

Trigger when given a `{business_name, city, website}` triple in the deep-
dive phase. Skip if there's no website domain (you can't propose an
email pattern without one).

## Tools provided

- `search_owner(business_name: str, city: str)` — Tavily search for the
  owner / GM. Returns `{query, hits}` like voice_of_customer.
- `guess_email_from_name(first_name: str, last_name: str, domain: str)`
  → `{best_guess: "...", candidates: [...]}` — common cold-email patterns
  (`first.last@`, `flast@`, `first@`).

## Workflow

1. `search_owner(business_name, city)` — query like
   `"<business> owner OR founder OR GM <city>"`.
2. From snippet text, extract a single first + last name. Look for:
   - "<Name> is the owner of …", "founded by <Name>", "<Name>, GM of …"
   - LinkedIn snippets ("<Name> | Owner at <Business> | LinkedIn")
   - Press / interviews
3. **Confidence rating** — set one of:
   - `high`     — explicit "owner" or "founder" claim with name in 2+
                  independent snippets
   - `medium`   — name appears in one credible snippet (LinkedIn, news)
   - `low`      — name guessed from a general bio or staff page
   - `unknown`  — no plausible name found
4. If `unknown`, return `{name: null, confidence: "unknown", email_guess:
   null, candidates: []}` and stop. Don't fabricate a name.
5. Otherwise, call `guess_email_from_name(first_name, last_name,
   <domain from website>)` and include both the `best_guess` and the full
   `candidates` list.

Return:

```json
{
  "business_name": "Mia's Salon",
  "name":          "Maya Iyer",
  "title":         "Owner",
  "confidence":    "medium",
  "evidence":      [{"title": "...", "url": "..."}],
  "email_guess":   "maya.iyer@miassalon.com",
  "email_candidates": ["maya.iyer@...", "miyer@...", "maya@..."]
}
```

## Rules

- **Always stamp `confidence` honestly.** A wrong name destroys the
  whole pitch's credibility. Err toward `low` / `unknown`.
- **Never invent a name.** "Probably owned by a Smith family" is not a
  finding.
- The email is a **guess**, not a fact. The downstream UI labels it as
  such. Always provide `candidates` so the user can pick a different
  pattern if their first try bounces.
- Domain extraction: take the registrable domain from the website URL —
  `https://www.miassalon.com/booking` → `miassalon.com`.