Enrich Contact

Enrich Contact

Look up a person in Lusha and return a call-ready contact card. Phone numbers — direct line and mobile — lead the output.

Step 1 — Parse Input

Extract all available identifiers from the user's request. contacts_search accepts three lookup paths:

• Email — standalone, strongest match
• LinkedIn URL — standalone, strong match
• First name + last name + company name — all three required together

A job title alone is not a lookup path. If the user gives only a title + company (e.g. "the CFO of Stripe"), there is no name to look up — first surface candidates with prospecting_contact_search (jobTitles + company), then enrich the chosen one. Only ask for clarification when no usable identifier is present at all.

Step 2 — Look Up and Reveal

contacts_search has an enrich flag that controls whether the call reveals (and charges for) phones and email. Pick the path by how confident the match is — never do both for the same person, that reveals and charges twice.

One-shot (preferred when the identifier is unambiguous — an email, a LinkedIn URL, or a clean name + company): Call contacts_search with enrich: true (the default). The response returns the profile with verified phones and email in a single call. You're done — do not call prospecting_contact_enrich afterward.

Preview-then-reveal (when the match may be ambiguous — common name, no company, multiple likely people):

1. Call contacts_search with enrich: false — this returns a preview only and consumes no reveal credits.
2. If multiple candidates come back, present the top 2–3 and ask the user to confirm.
3. Call prospecting_contact_enrich with the chosen result's id and reveal set from its canReveal[].field to reveal phones and email once.

Step 3 — Fetch Signals (optional)

If you resolved a Lusha contact id in Step 2, use signals_contacts_get with that id to check for recent signals (promotion, company change). If you only have an email or LinkedIn URL and no id, use signals_contacts_search instead. Signals default to the last 6 months. Include any returned signals in the output as context.

Step 4 — Present the Contact Card

Format output as follows. Phone numbers appear first — never buried.

---

[Full Name] · [Title] · [Company]

📞 Phone

✉️ Email

Company

Signals (if returned)

• [Signal type] — [date]

---

Omit any section where no data was returned. Never show blank rows.

If no phone numbers are available, state this explicitly: "No verified phone numbers found for this contact." Do not present the card as complete when phones are missing.

Step 5 — Offer Next Actions

Ask the user which action to take next:

1. Find colleagues — search for more contacts at the same company
2. Find similar contacts — build a lookalike list using this person as a seed
3. Signal-prospect from this company — check if their company is showing buying signals

If the user selects "Find similar contacts"

The lookalike model requires at least 5 reference contacts or companies to produce quality results. With only 1 contact enriched so far, ask the user how they want to build the reference set before proceeding:

"To find similar contacts I need at least 5 references for the lookalike model. How would you like to provide them? A) I'll pull colleagues from [Company] — you pick which ones to include B) I have a specific list of contacts or companies to use as references"

If the user chooses A: Use prospecting_contact_search scoped to the same company (pass the company via companyNames or companyDomains) to retrieve colleagues. Present the results and ask the user to select which to include alongside the original contact. Proceed to lookalike-prospect once ≥5 are confirmed.

If the user chooses B: Ask the user to provide their list. Validate that ≥5 are supplied before calling lookalike-prospect. If fewer than 5 are provided, state how many more are needed and wait — do not proceed.

In either case, do not call any lookalike tool until the reference set has been confirmed at ≥5.