Systems Lab

Agent skill

cold-email-lemlist

Cold email skill for Claude Code and Codex: build a targeted B2B prospect list with Vibe Prospecting, enrich it with firmographics and verified work emails, write a personalized icebreaker and email per prospect from their real company data, and push every lead into a live Lemlist campaign with personalization variables pre-filled.

activeNeeds a keyActs undeclared1,628 words

Filed under Outbound email.

From explorium-ai/gtm-skills · 22 skill entries · 200 · pushed 2026-10-11

What it does when it runs

Cold email skill for Claude Code and Codex: build a targeted B2B prospect list with Vibe Prospecting, enrich it with firmographics and verified work emails, write a personalized icebreaker and email per prospect from their real company data, and push every lead into a live Lemlist campaign with personalization variables pre-filled. Use for cold outbound, email personalization at scale, and Lemlist campaign setup. Triggers on 'cold email campaign', 'push leads to Lemlist', 'write personalized outbound emails', 'build a Lemlist sequence'. Works in Claude Code, Codex, Grok, and Claude Cowork.

Automated analysis of the skill and the 0 files bundled beside it. A skill’s own description is written to be selected by an agent, so it describes the job and not the dependencies.

Keys and connectors you must supply
  • API_KEY
  • LEMLIST_API_KEY
  • YOUR_VP_API_KEY
  • mcp__*__fetch-entities
Hosts it reaches
  • api.lemlist.com
Tool permissions it declares
No allowed-tools in the frontmatter. It does act, so it runs under whatever permissions your session already grants.
Actions present in the files
shell

Ask about cold-email-lemlist

Opens your assistant with this page's verified links already in the prompt.

Is this safe to install?ClaudeChatGPT
Adapt it to my stackClaudeChatGPT
What else do I need for it to workClaudeChatGPT
Rather ask a human? Talk to Cheetah
git clone --depth 1 --filter=blob:none --sparse https://github.com/explorium-ai/gtm-skills.git /tmp/gtm-skills
git -C /tmp/gtm-skills sparse-checkout set "skills/cold-email-lemlist"
mkdir -p ~/.claude/skills/cold-email-lemlist
cp -R "/tmp/gtm-skills/skills/cold-email-lemlist/." ~/.claude/skills/cold-email-lemlist/

Picked up without a restart. A project skill of the same name is shadowed by your personal one. For one repository only, swap ~/.claude/skills for .claude/skills. Claude Code docs ↗

Or take the whole library

This repo ships a .claude-plugin manifest, so Claude Code can install all 22 skills at once. Plugin skills are invoked as /<plugin>:<skill>, so they never collide with your own.

/plugin marketplace add explorium-ai/gtm-skills
/plugin

The folder is the same in every client that implements the format — 46 of them — so if yours is not above, only the destination changes.

Before you install: this skill will not complete its job on a bare agent. It needs mcp__*__fetch-entities, API_KEY, LEMLIST_API_KEY, YOUR_VP_API_KEY, which you have to obtain separately.

Reproduced in full from explorium-ai/gtm-skills/blob/8b9a83b05a738356cbdf285589ae2afb3794ac74/skills/cold-email-lemlist/SKILL.md, which is licensed MIT (repository). 1,628 words, 19 headings.

Cold Email — Vibe Prospecting + Lemlist

Build a targeted prospect list, enrich it with firmographic and contact data, have Claude write personalized emails for each prospect, and push everything to a live Lemlist campaign — ready to send.

What you'll end up with:

  • A filtered, enriched prospect list with verified work emails
  • A personalized first-line (icebreaker) and full email per prospect, written by Claude using their actual company data
  • All leads uploaded to a Lemlist campaign with personalization variables pre-filled

Step 0 — Credential Check (Claude: always do this first)

Do not start Phase 1 until both checks pass.

Vibe Prospecting

Cowork mode: look for a tool matching mcp__*__fetch-entities in your tool list.

  • ✅ Found → proceed
  • ❌ Missing → tell the user: "Please connect the Vibe Prospecting connector from the connector store, then let me know when it's done." Wait. Do not continue until the tool appears.

Claude Code / terminal:

npx @vibeprospecting/vpai@latest --help
  • ✅ Lists tools → proceed
  • ❌ Error → run: npx @vibeprospecting/vpai@latest config --api-key "YOUR_VP_API_KEY"

Lemlist API Key

Ask the user: "Please paste your Lemlist API key. I'll verify it and we'll get started."

Get it from: Lemlist → Settings → Integrations → API.

Once provided, verify:

export LEMLIST_API_KEY="<key-from-user>"

curl -s "https://api.lemlist.com/api/team" \
  -u ":$LEMLIST_API_KEY" \
  | python3 -c "
import json, sys
d = json.load(sys.stdin)
print('✅ Connected —', d.get('name', 'team found')) if '_id' in d else print('❌ Failed:', d.get('message', 'unknown error'))
"
  • ✅ Connected → tell the user "Both credentials verified — let's go." Proceed to Phase 1.
  • ❌ Failed → ask the user to check the API key in Lemlist → Settings → Integrations → API. Do not proceed.

Phase 1 — Define Your ICP and Fetch Prospects

Ask the user for their targeting criteria if not already provided:

"Who are we targeting? Tell me: industry, company size, geography, job titles/levels, and any tech stack or funding signals you want to filter on."

Then run autocomplete for any controlled-vocab fields before fetching.

# Normalize industry/category values first
npx @vibeprospecting/vpai@latest autocomplete \
  --args '{"field": "linkedin_category", "query": "<user industry>"}' \
  --tool-reasoning 'Normalize industry filter for cold email prospect list'

# Normalize job titles if needed
npx @vibeprospecting/vpai@latest autocomplete \
  --args '{"field": "job_title", "query": "<user job title>"}' \
  --tool-reasoning 'Normalize job title for cold email prospect list'

Sample 5 prospects first (full chain — do not stop after fetch to ask for approval):

npx @vibeprospecting/vpai@latest fetch-entities --all-parameters

npx @vibeprospecting/vpai@latest fetch-entities \
  --args '{
    "entity_type": "prospects",
    "filters": {
      "job_level": {"values": ["<user levels>"]},
      "job_department": {"values": ["<user departments>"]},
      "linkedin_category": {"values": ["<normalized category>"]},
      "company_headcount_range": {"values": ["<user size range>"]},
      "company_country_code": {"values": ["<user geo>"]},
      "has_email": true
    }
  }' \
  --number-of-results 5 \
  --tool-reasoning '<user request verbatim>'

Note the session_id and table_name from the output — pass these to every subsequent step.

Run the full enrich chain on those 5 (Phase 2), show the result as a table, then ask: "Does this look right? How many prospects do you want in the full run?" Only after approval re-run at full scale.


Phase 2 — Enrich with Contact Info

Enrich the fetched prospects with verified work email, LinkedIn URL, and direct phone.

npx @vibeprospecting/vpai@latest enrich-prospects --all-parameters

npx @vibeprospecting/vpai@latest enrich-prospects \
  --args '{"enrichments": ["contacts", "profiles"]}' \
  --session-id <SESSION_ID> \
  --table-name <TABLE_NAME_FROM_FETCH_STEP> \
  --tool-reasoning '<user request verbatim>' \
  --csv

Drop any prospects where work_email is empty — Lemlist requires a valid email to add a lead.

Output: prospects-enriched.csv — columns include first_name, last_name, work_email, linkedin_url, job_title, company_name, company_domain, employee_count, annual_revenue, tech_stack, last_funding_type


Phase 3 — Write Personalized Emails

Read prospects-enriched.csv and write a personalized email for each prospect using their actual company data. Do not use generic templates — each email should reference something specific to that company.

Ask the user for:

"What's the core value prop you want to lead with? And is there a specific pain point, use case, or trigger (e.g. recent funding, tech stack) you want to reference?"

For each prospect, write:

1. Icebreaker (1 sentence) — a specific, researched opening line referencing something real about their company. Examples of what to use:

  • Their tech stack (e.g. "Noticed you're running Salesforce + HubSpot...")
  • Company size/growth signal (e.g. "With [X] employees and growing...")
  • Funding event (e.g. "Congrats on the Series B — scaling RevOps is usually top of mind at that stage...")
  • Industry-specific angle

2. Email body — 4–6 sentences max. Structure:

  • Icebreaker (from above)
  • One-sentence value prop tied to their context
  • One-sentence social proof or specific outcome
  • Clear, low-friction CTA (e.g. "Worth a 15-min call this week?")

3. Subject line — short, specific, not salesy. Under 8 words.

Write all output to prospects-emails.csv, adding these columns to the enriched data:

ColumnDescription
icebreakerPersonalized first line
email_subjectSubject line
email_bodyFull email body

Example output row:

FieldValue
icebreakerNoticed you're running Salesforce and recently closed a Series A — congrats.
email_subjectfaster pipeline data for [company]
email_bodyNoticed you're running Salesforce and recently closed a Series A — congrats. At that stage, RevOps teams usually hit a wall with stale CRM data slowing down outbound. Explorium helps teams like yours enrich and score their entire HubSpot or Salesforce account base in under an hour, so reps are always working the right accounts. Happy to show you a quick example with your actual ICP. Worth a 15-min call this week?

After writing all emails, show a table of 3–5 sample rows for the user to review before uploading. Ask: "Does the tone and personalization feel right? Any tweaks before I push to Lemlist?"


Phase 4 — Create Lemlist Campaign

Create a new campaign in Lemlist to hold these prospects, or ask the user if they want to add to an existing one.

Option A — Create a new campaign

# Create campaign
CAMPAIGN=$(curl -s -X POST "https://api.lemlist.com/api/campaigns" \
  -u ":$LEMLIST_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Vibe Prospecting — <ICP description> — <date>",
    "type": "email"
  }')

echo $CAMPAIGN | python3 -c "import json,sys; d=json.load(sys.stdin); print('Campaign ID:', d.get('_id','error'))"
export LEMLIST_CAMPAIGN_ID="<campaign _id from above>"

Option B — Use an existing campaign

# List existing campaigns
curl -s "https://api.lemlist.com/api/campaigns" \
  -u ":$LEMLIST_API_KEY" \
  | python3 -c "
import json, sys
for c in json.load(sys.stdin):
    print(c['_id'], '—', c['name'])
"

# User picks one → set it
export LEMLIST_CAMPAIGN_ID="<chosen campaign id>"

Phase 5 — Upload Leads to Lemlist

Add each prospect from prospects-emails.csv to the campaign. Lemlist accepts custom variables per lead — use these to carry the personalized icebreaker and email copy into the campaign.

import csv, json, os, requests, time

API_KEY = os.environ["LEMLIST_API_KEY"]
CAMPAIGN_ID = os.environ["LEMLIST_CAMPAIGN_ID"]
AUTH = ("", API_KEY)

with open("prospects-emails.csv") as f:
    prospects = list(csv.DictReader(f))

success, failed = 0, []

for p in prospects:
    email = p.get("work_email", "").strip()
    if not email:
        continue

    payload = {
        "firstName":    p.get("first_name", ""),
        "lastName":     p.get("last_name", ""),
        "companyName":  p.get("company_name", ""),
        "linkedinUrl":  p.get("linkedin_url", ""),
        # Custom variables — reference these in your Lemlist email template
        # as {{icebreaker}}, {{emailBody}}, {{emailSubject}}
        "icebreaker":   p.get("icebreaker", ""),
        "emailBody":    p.get("email_body", ""),
        "emailSubject": p.get("email_subject", ""),
    }

    resp = requests.post(
        f"https://api.lemlist.com/api/campaigns/{CAMPAIGN_ID}/leads/{email}",
        auth=AUTH,
        json=payload
    )

    if resp.status_code in (200, 201):
        success += 1
    elif resp.status_code == 429:
        print("Rate limited — waiting 5s")
        time.sleep(5)
        resp = requests.post(
            f"https://api.lemlist.com/api/campaigns/{CAMPAIGN_ID}/leads/{email}",
            auth=AUTH, json=payload
        )
        if resp.status_code in (200, 201):
            success += 1
        else:
            failed.append({"email": email, "error": resp.text})
    else:
        failed.append({"email": email, "error": resp.text})

print(f"\n✅ {success} leads uploaded")
if failed:
    print(f"❌ {len(failed)} failed:")
    for f in failed: print(" ", f["email"], "—", f["error"])

After upload, tell the user:

"[N] leads are now in your Lemlist campaign. Before you launch, make sure your email template in Lemlist uses {{icebreaker}}, {{emailBody}}, and {{emailSubject}} as variables so the personalization populates correctly. You'll also want to set your sending schedule and daily limits in Lemlist before activating."


Full Checklist

[ ] Step 0  — Vibe Prospecting connected, Lemlist API key verified
[ ] Phase 1 — ICP defined, prospect list fetched (sample approved)
[ ] Phase 2 — Prospects enriched with verified emails and company data
[ ] Phase 3 — Personalized emails written and reviewed
[ ] Phase 4 — Lemlist campaign created or selected
[ ] Phase 5 — Leads uploaded with personalization variables
[ ] Done    — Review campaign in Lemlist, set schedule, activate

Lemlist Template Setup (one-time)

In your Lemlist campaign, your email step should use these variable placeholders:

Subject: {{emailSubject}}

{{icebreaker}}

{{emailBody}}

This lets Claude's personalized copy flow directly into each lead's email without any manual editing.


Troubleshooting

ProblemSolution
Vibe Prospecting tools missingConnect from connector store; wait for mcp__*__fetch-entities to appear
Lemlist 401 UnauthorizedAPI key wrong — regenerate in Lemlist → Settings → Integrations → API
Lemlist 404 on lead uploadCampaign ID is wrong — re-check with the list campaigns call in Phase 4
Lead already exists errorLemlist returns 409 if the email is already in the campaign — safe to ignore
Low match rate / missing emailshas_email: true filter in Phase 1 ensures only contactable prospects are fetched
Emails feel genericGive Claude more context in Phase 3: specific pain points, recent company news, or competitor context
Lemlist rate limitsAPI allows ~120 req/min — the script handles 429s with retry; for very large lists add time.sleep(0.5) between calls

Other skills for the same job

Different authors, same problem. Matched on the words in the skill name, across every library in the catalogue except this one.

Need help setting it up?

This page tells you what cold-email-lemlist does and what it needs. Cheetah builds the agent setup it runs inside: data, CRM, sequencing and the guardrails.

Book a call →

The directory stays free. There is nothing gated behind this.