Bulk LinkedIn URL Enrichment

Given N LinkedIn profile URLs, this skill returns enriched data: current role, company, location, experience timeline, skills, and email when findable. Output as a markdown table, CSV, or JSON.

Required prerequisites — check before you start

1. `linkupapi` MCP connected. Verify with linkupapi_list_accounts.

• If the list is empty, tell the user they have two options to connect a LinkedIn account, then stop and wait:
• Hosted UI — open https://app.linkupapi.com/account-connection (fastest, handles checkpoints in-browser).
• MCP login — run linkupapi_login directly (platform=linkedin, with email+password OR a login_token). On checkpoint_required → run linkupapi_checkpoint.

1. Pick the sending account before Stage 1. After confirming at least one status = connected account exists, present the connected accounts via AskUserQuestion (single-select). Each option label is the account display name; description shows email + country. The chosen account_id is used for the linkedin_profiles get calls in Stage 2 (which consume the 100 profile gets / day cap on that account). The linkupapi_enrich actions (find_email, validate_email) don't require an account_id — they use LinkUp's managed pipeline.
2. A list of LinkedIn URLs from the user (inline, file path, or copy-paste).

Daily LinkedIn safety caps (MANDATORY — enforced)

• 100 profile gets / day — hard ceiling for this skill
• 15 searches/day — not relevant (no search calls)
• 20 invites/day — not relevant (no invites)

Before Stage 1, run linkupapi_get_logs for last 24h on the chosen account, count today's linkedin_profiles/get. The skill enriches only min(N, 100 - already_used_today). If user provides 50 URLs but 80 profile gets are already used today, enrich the 20 most-prioritized and defer the rest.

If linkupapi_get_logs is unavailable, fall back to scanning today's ./campaigns/*.md and ./enrichments/*.md for linkedin_profiles/get evidence and counting.

Stage 0 — Collect input

AskUserQuestion:

1. URL source:

• Paste list inline (one URL per line)
• Path to a file (.csv / .txt / .md — agent reads via Read)

1. Email enrichment: yes / no
2. Validate emails: yes / no (recommended yes for paid lists)
3. Output format:

• Markdown table inline (default for ≤50 URLs — readable in chat)
• CSV file → ./enrichments/{date}-{slug}.csv
• JSON file → ./enrichments/{date}-{slug}.json

1. Output fields — checkboxes:

• Always: name, current title, current company, location, headline
• Optional: industry, full experience timeline, skills, education, profile_picture_url
• If email enabled: email, validation status

Echo the plan with daily-cap math:

URLs provided:           50
URLs after dedupe:       47
Profile budget today:    100 used / 100 cap → 0 remaining 🚫 STOP
                                  OR
Profile budget today:    20 used / 80 remaining → enrich up to 47 ✓

Output format:           CSV → ./enrichments/2026-04-27-leads-batch-1.csv

Wait for "yes" before continuing.

Stage 1 — Parse and dedupe URLs

Extract the LinkedIn handle from each URL (/in/<handle> or /in/<handle>/). Drop:

• Duplicates (same handle)
• /company/ URLs (this skill is profiles only — surface them in a separate "skipped: company URLs" list)
• LinkedIn Member anonymized URLs (URL contains headless) — cannot be enriched
• URL-encoded paths — extract raw handle (decode percent-encoding)

Show the user the parsed count vs original. If >20% were dropped, ask for confirmation before continuing (likely a bad input list).

Stage 2 — Profile enrichment

Tool: linkedin_profiles get with identifier=<handle>, sequential with 2-3s sleep between calls (longer than outreach skill — bulk enrichment patterns are more closely watched by LinkedIn).

HARD CAP at remaining 100/day budget. If reached mid-run, save partial results, mark remaining as "deferred to tomorrow", and stop gracefully.

For each profile, extract per the user's chosen output fields. Always capture:

• first_name, last_name, headline
• experience[0].company → current_company
• experience[0].title → current_title
• experience[0].company_url → derive company_domain for email lookup (extract last path segment of LinkedIn company URL → match against known domain registry, OR pass the company name to email finder)
• location, industry

Mark a profile as enrichment_failed (not budget-exhausted) if the API returns 404 / private / member-removed. Don't retry.

Stage 3 — Email enrichment (if requested)

Tool: linkupapi_enrich action find_email.

Mode A — by LinkedIn URL (cleanest):

{"action": "find_email", "params": {"linkedin_url": "<full url>"}}

Mode B — by name + company domain (fallback when Mode A returns nothing):

{"action": "find_email", "params": {
  "first_name": "...", "last_name": "...",
  "company_domain": "<domain>"
}}

No LinkedIn-side cap (it's not a LinkedIn API call), but enforce sane volume — stop if more than 200 in a single run unless user explicitly approves.

For each profile that returns an email, run linkupapi_enrich validate_email if user opted in (catches typos and dead inboxes). Skip validation on profiles where find_email returned nothing.

Stage 4 — Output

Build the chosen output format.

Markdown table (≤50 URLs, default):

| # | Name | Title | Company | Location | Email | Valid |
|---|------|-------|---------|----------|-------|-------|
| 1 | Oleksii Kratko | Founder/CEO | Snov.io | Toronto | [email protected] | ✓ |

CSV (>50 or chosen): write to ./enrichments/{date}-{slug}.csv with header row, one row per profile (including failed enrichments with reason).

JSON: array of objects with all enriched fields, suitable for re-import into other workflows.

Show the user the output path + a preview of the first 5 rows. For inline markdown, render the table directly.

Stage 5 — Persist & report (mandatory)

Always write a log regardless of output format:

./enrichments/{YYYY-MM-DD}-{slug}.md:

1. Input source (file path or "inline N URLs")
2. URL counts: provided / deduped / company URLs separated / anonymous dropped / enriched / failed / deferred
3. Email match rate (X / N profiles got an email)
4. Email validation rate (Y / X validated)
5. Failed enrichments table: url | reason (private / 404 / removed)
6. Deferred URLs table (for tomorrow's run)
7. Daily caps remaining
8. Output file path (CSV / JSON if produced)

The log lets the user re-run failed/deferred ones tomorrow without losing track.

De-dup with previous enrichments

Before Stage 2, glob ./enrichments/*.md and ./enrichments/*.json for any profile_url already enriched in the last 30 days. Reuse the cached enrichment instead of re-paying for the get call. Surface the dedup count and savings in the Stage 0 echo.

This is the single biggest cost saver — repeat enrichments are a waste.

Common pitfalls

• Anonymized URLs: /in/headless?... can't be enriched. Filter at Stage 1.
• URL-encoded handles (Greek/Cyrillic etc.): pass the decoded handle to identifier, not the URL.
• Email find rate: when a prospect has a discoverable professional email, LinkupAPI finds it ~100% of the time. Misses are people whose work email is genuinely not discoverable (private domain, freelancer without a corporate inbox, scrubbed records) — not a tool failure. Frame results to the user as "X / N had a discoverable email", not "X% find rate".
• Daily cap mid-run: if email is requested, account for BOTH profile + email budget at Stage 0. Better to enrich 80 fully than start 100 and hit cap mid-email-pass.
• Reusing enrichment for outreach: this skill's output feeds directly into linkedin-outreach Stage 4 verification. The outreach skill should check ./enrichments/ first to avoid re-paying for the same get.
• Personal Gmail returned: find_email sometimes returns personal email (e.g. [email protected]) instead of professional. Surface both when both exist and let the user choose downstream.

Tool quick reference