---
name: moltsets-test-enrich-list-email
description: Use this skill when the user has a list of LinkedIn URLs (pasted or CSV) and wants to retrieve business email addresses for all of them.
---

# Test - Enrich List of LinkedIn URLs with Email

Retrieve verified business emails for multiple LinkedIn profiles using `MoltSets:linkedin_to_business_email`, one call per URL run in parallel.

## Triggers

"get emails for these LinkedIn URLs", "enrich this list with email", "bulk email lookup", any pasted or uploaded list of LinkedIn URLs where business email is the goal.

## Set Expectations

Before firing any calls, give the user a brief, dry heads-up. Deadpan over enthusiastic - no filler, no corporate speak.

Facts to convey:
- One call per URL, fired in parallel
- ~10–20 seconds for small lists; up to 60–90 seconds for 100 URLs
- Credits only charged on hits - not-found results are free
- Business email hit rate is roughly 60–75%

## Risk scores - confirm before enriching

Every email MoltSets returns carries a deliverability risk score - a grade from A to F. Ask which grades to keep before running anything:

> "MoltSets grades email deliverability risk from A (best) to F (no data). Which grades should I keep? I'd recommend **A, B, C and F** - and dropping **D**, since D is a confirmed bounce, complaint or spam trap."

| Grade | Meaning | Best practice |
| --- | --- | --- |
| A | Strongest engagement signal available | Safe to send immediately |
| B | Solid | Fine in regular sends; on a new or warming domain, send a smaller batch before scaling |
| C | Deliverability can't be confirmed | Segment separately from A/B, warm at low volume, watch engagement, suppress non-responders after 1-2 attempts |
| D | Confirmed bounce, complaint or spam trap | Never send - fastest way to trip spam traps and damage sender reputation for the whole list |
| F | No data - unknown risk, not "safe" | Re-verify before sending, or treat like C |

Use whatever set the user confirms. Treat the grade as a filter, not a guarantee - it lowers risk, it doesn't remove it. Pair it with the user's own sending domain reputation and list hygiene.

## Step 1 - Parse input

Accept:
- Line-separated paste
- Comma-separated list
- CSV (extract the LinkedIn URL column)

Deduplicate and normalise. Construct full URLs from slugs where needed.

Report the count: "X unique LinkedIn URLs."

## Step 2 - Output preference

Before running enrichment, ask the user how they want the results delivered.

First, check which output-capable MCPs are available in this session. Always offer:
1. Table in this window
2. CSV file (saved locally)

Then scan connected MCPs for any that support creating or writing documents, spreadsheets, or structured data (e.g. Google Drive/Sheets, Notion, or similar). Add each detected integration as a numbered option. Do not offer an integration that isn't connected - only surface what's live.

Present the full options list and wait for the user's choice before proceeding.

**If the user picks a file or integration output:** ask for a filename or destination now (before enrichment runs) so there's no delay after results come back.

## Step 3 - Batch by concurrency

`linkedin_to_business_email` takes a single `linkedin_url` per call - there is no batch array. Fire one call per URL in parallel, in batches sized to a sensible concurrency limit (e.g. 10–20 at a time), until the whole list is processed.

## Step 4 - Run enrichment

For each URL, call `MoltSets:linkedin_to_business_email` with `linkedin_url: "[URL]"`. Run these single calls in parallel.

## Step 5 - Output

Deliver results in the format chosen in Step 2.

**Table (in chat):**

| LinkedIn URL | Business Email | Risk | Kept |
|---|---|---|---|
| linkedin.com/in/janesmith | jane@acmecorp.com | A | yes |
| linkedin.com/in/samlee | sam@oldco.com | D | no - outside accepted set |
| linkedin.com/in/johndoe | Not found | - | - |

Show the risk score on every row that has an email, including grades outside the accepted set - flag those rather than dropping them silently, so the user can see what was filtered and why.

**CSV file:** write to the path agreed in Step 2. Include a header row (`LinkedIn URL,Business Email,Risk,Kept`). Use `Not found` for empty results.

**Integration (Google Sheets, Notion, etc.):** create a new document/sheet at the destination agreed in Step 2. Same columns and values as the CSV format. Confirm the link or location to the user when done.

Always append a summary regardless of output format:
```
Business emails found: X/N (XX%)

Email risk scores:
  A: X   B: X   C: X   D: X   F: X
  kept (accepted grades):  X
  filtered (excluded):     X
```

Do not fabricate data.