athina-ai/linkedin-message-writer

LinkedIn Message Writer

Research LinkedIn leads and write personalized messages for any LinkedIn message type. Takes LinkedIn URLs, researches each person using Apify (profile + recent posts), and writes messages based on what it finds.

No LinkedIn cookies. No database setup. Just LinkedIn URLs in, personalized messages out.

When to Auto-Load

Load this skill when:

• User says "write LinkedIn messages", "LinkedIn outreach", "connect with these leads on LinkedIn", "send LinkedIn messages"
• User has a list of LinkedIn URLs and wants to reach out
• User wants to write personalized connection requests, InMails, DMs, or comments

Prerequisites

Apify API Token

Required for researching LinkedIn profiles and posts. Set in .env:

APIFY_API_TOKEN=your_token_here

No LinkedIn cookies, login, or session tokens needed. Apify handles scraping without any LinkedIn credentials.

That's it. One env var. Nothing else.

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LinkedIn Message Types Reference

This skill writes any text-based LinkedIn message type. Each type has different constraints.

| Message Type | Who Can Receive | Character Limit | When to Use | |-------------|----------------|-----------------|-------------| | Connection request | 2nd/3rd degree connections | 200 (free) / 300 (premium) | First touch. Must earn the accept. No selling. | | InMail | Anyone (requires premium credits) | Subject: 200, Body: 1,900 | Standalone pitch to people who won't accept cold connections. Senior execs, busy people. | | DM | 1st-degree connections only | 8,000 | Follow-ups after connection accepted. Conversational, not broadcast. | | Message request | Group members, event attendees, #OpenToWork | 8,000 | Warm context — you share a group or event. Reference the shared context. | | Post comment | Anyone (public posts) | 1,250 | Warm-up before connecting. Show you engaged with their content. Not a pitch. | | Comment reply | Anyone (in a thread) | 1,250 | Engage in a conversation they started. Add value, don't pitch. |

Key Rules Per Type

Connection request (200/300 chars):

• This is the gatekeeper. If they don't accept, nothing else happens.
• Lead with the signal — what they did/said/posted that caught your attention.
• One sentence of relevance. No pitch, no CTA, no "I'd love to..."
• MUST be under the character limit. Count every character. If over, rewrite — never truncate.
• Free accounts: 200 chars. Premium/Sales Navigator: 300 chars. Ask the user which they have.

InMail (subject 200 + body 1,900 chars):

• Must work standalone — they haven't accepted your connection.
• Subject: curiosity-driven, not salesy. Not "Quick question" or "Partnership opportunity."
• Body: include context for why you're reaching out (the signal). Be specific.
• Higher commitment ask is OK here — you're using a premium credit.

DM (8,000 chars):

• Conversational. These read like DMs, not emails.
• Shorter is almost always better. A 2-sentence message outperforms a 5-sentence one.
• Good for follow-up sequences after connection accepted.
• Sequence structure: Day 0 connection → Day 3 value-first → Day 7 social proof → Day 14 breakup.

Message request (8,000 chars):

• Always reference the shared context (group name, event name, OpenToWork status).
• More casual than InMail since you have something in common.

Post comment (1,250 chars):

• Add genuine value. Share an insight, ask a smart question, build on their point.
• NOT "Great post!" or "Love this!" — that's noise.
• This is a warm-up move, not a pitch. The goal is to get noticed before connecting.

Comment reply (1,250 chars):

• Continue the conversation. Reference what they said specifically.
• Shorter than a standalone comment. 2-3 sentences max.

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Workflow

Phase 0: Intake

Ask the user these questions. Skip any already answered.

Leads:

1. Where are your leads? (CSV file, paste LinkedIn URLs, database, CRM — whatever they have)
2. How many leads? (affects cost estimate and whether to use post scraper)

Message type: 3. What kind of LinkedIn message do you want to write? (connection request, InMail, DM, message request, post comment, comment reply, or a sequence of multiple types) 4. If connection request: do you have a free or premium LinkedIn account? (affects character limit: 200 vs 300)

Goal: 5. What's the objective? (book meetings, drive demo requests, get replies, build relationships, promote content, warm up before outreach) 6. What's the angle or hook? (pain-based, hiring signal, competitor displacement, event-based, content engagement, mutual connection, cold)

Tone: 7. Which tone? Present options:

• Casual Professional — Friendly, human, slightly informal. Like messaging a peer. (default)
• Thought Leader — Lead with insight or a contrarian take. Position sender as expert.
• Provocative — Challenge assumptions, pattern-interrupt. Higher risk, higher reward.
• Enterprise Formal — Polished, structured. For regulated industries or C-suite targets.
• Custom — User pastes reference messages that have worked, or describes the vibe.

8. Any reference messages that have worked well? (these override tone presets)

Context: 9. What does your company/product do? (one-liner for the AI to work with) 10. Any proof points? (customer names, metrics, case studies to reference)

Output: 11. Which LinkedIn outreach tool do you use? (Dripify / Expandi / Botdog / PhantomBuster / Just give me a CSV)

Phase 1: Load Leads

Accept leads from whatever source the user provides:

• CSV file: Read the CSV. Look for a column containing LinkedIn URLs (common names: linkedin_url, LinkedIn URL, LinkedIn, profile_url, url). If ambiguous, ask the user which column.
• Pasted URLs: User pastes LinkedIn URLs directly. Parse them.
• Pasted list: User pastes names + companies or other data. Extract what's available.
• Database/CRM: Ask the user how to access it. Use whatever tool or export they provide.

Minimum required: At least one LinkedIn URL per lead.

Present the lead count to the user and confirm before proceeding to research.

Phase 2: Research

Research each lead using two Apify actors. Both require only APIFY_API_TOKEN — no LinkedIn cookies.

Step 1: Profile Data

Use harvestapi/linkedin-profile-scraper to get profile data for all leads.

API call:

curl -X POST "https://api.apify.com/v2/acts/harvestapi~linkedin-profile-scraper/runs?token=$APIFY_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "urls": [
      {"url": "https://www.linkedin.com/in/PROFILE_1/"},
      {"url": "https://www.linkedin.com/in/PROFILE_2/"}
    ]
  }'

Cost: $0.003 per profile. 100 leads = $0.30.

Returns per lead:

• firstName, lastName, headline
• jobTitle, companyName, companySize, companyIndustry
• Full work history (positions array with title, company, description, duration)
• Education (schools, degrees)
• Skills (with endorsement counts)
• Location, followerCount, connectionsCount
• isCreator, isPremium, isVerified flags

Polling for results:

# Check run status
curl "https://api.apify.com/v2/acts/harvestapi~linkedin-profile-scraper/runs/{RUN_ID}?token=$APIFY_API_TOKEN"

# When status is SUCCEEDED, fetch results
curl "https://api.apify.com/v2/datasets/{DATASET_ID}/items?token=$APIFY_API_TOKEN"

Step 2: Recent Posts (Optional)

Use harvestapi/linkedin-profile-posts to get recent posts. Run this when:

• User asks for deep personalization
• Lead count is small (under 50) and budget allows
• User explicitly wants to reference what leads are posting about

Skip this when:

• Lead count is large (100+) and user wants speed over depth
• User says basic personalization is fine

API call:

curl -X POST "https://api.apify.com/v2/acts/harvestapi~linkedin-profile-posts/runs?token=$APIFY_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "profileUrls": [
      "https://www.linkedin.com/in/PROFILE_1/",
      "https://www.linkedin.com/in/PROFILE_2/"
    ]
  }'

Cost: $0.002 per post. ~20 posts per profile = ~$0.04 per lead. 50 leads = $2.00.

Returns per post:

• content (full post text)
• engagement (likes, comments, shares, reaction breakdown)
• postedAt (timestamp)
• postImages (if any)
• author info (name, headline)

Polling: Same pattern as Step 1.

Step 3: Present Research Summary

After research completes, present a summary table:

Leads researched: {count}
Profile data: {count} profiles retrieved
Posts scraped: {count} posts from {count} leads (or "skipped")
Research cost: ~${total}

Sample leads:
| Name | Title | Company | Recent Post Topic | Personalization Angle |
|------|-------|---------|-------------------|----------------------|
| Jane Smith | VP Sales | Acme Corp | Posted about AI in sales | Reference her AI post |
| ... | ... | ... | ... | ... |

If the user asked to filter/qualify leads, do that now based on profile data (title, company, industry, etc.) and present which leads made the cut.

Phase 3: Write Messages

Generate personalized messages for each lead based on the research.

Personalization Hierarchy

Use the best available signal for each lead. In order of strength:

1. Recent post content — Reference a specific post they wrote. Strongest signal.
2. Work history details — Reference a specific achievement from their profile (e.g., "scaled from 0 to $8M GMV" is better than "you're a Co-founder").
3. Creator topics/hashtags — Reference what they post about broadly.
4. Current role + company — Reference their current position and what the company does.
5. Education/background — Mutual school, shared background. Weakest but still personal.

If the user provided reference messages that have worked, analyze those for tone, length, structure, and vocabulary. Use them as the template — don't override with defaults.

Writing Process

1. Generate samples first. Write messages for 3-5 leads with different signal richness levels. Present to user.
2. Iterate. User reviews, gives feedback. Adjust tone/approach. Max 3 rounds.
3. Batch generate. After approval, write messages for all remaining leads.

Character Limit Enforcement

After generating any message, count the characters. If over the limit:

• Rewrite from scratch. Do NOT truncate.
• Truncated messages look broken and unprofessional.
• For connection requests (200/300 chars), every character matters. Be ruthless.

Phase 4: Export

Universal CSV Format

Generate a CSV with these columns:

linkedin_url, first_name, last_name, company, title, message_type, message_subject, message_body

For sequence-based campaigns (connection + follow-ups), use:

linkedin_url, first_name, last_name, company, title, connection_request, followup_1, followup_2, followup_3, inmail_subject, inmail_body

Tool-Specific Formatting

Dripify:

• Columns: Profile URL, Note, Message 1, Message 2, Message 3
• One row per lead with all messages in separate columns

Expandi:

• Columns: LinkedIn URL, Connection message, Follow-up #1, Follow-up #2, Follow-up #3, InMail subject, InMail message

Botdog:

• Columns: linkedin_profile_url, connection_note, message_1, message_2, message_3

PhantomBuster:

• Columns: profileUrl, message
• PhantomBuster typically handles one action at a time — may need separate CSVs for connection + follow-ups

Generic CSV / Other:

• Use the universal format
• Ask the user what their tool expects and adjust if needed

Save Files

Save to the current working directory:

{campaign-name}-{YYYY-MM-DD}.csv

Phase 5: Review & Deliver

Present final summary:

Campaign: {name}
Message type: {type}
Leads: {count}
Tool: {dripify/expandi/etc.}
Personalization: {profile-only / profile+posts}
Research cost: ~${amount}
Export file: {file_path}

Show 3-5 sample messages from the export for final review.

Do NOT mark as done without explicit user confirmation. Ask: "Messages look good? Anything to adjust before you import?"

After confirmation:

• Provide the file path
• Give tool-specific import instructions
• Remind user to verify the first few messages after import

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Cost Estimates

| Leads | Profile Only | Profile + Posts | |-------|-------------|----------------| | 10 | ~$0.03 | ~$0.43 | | 50 | ~$0.15 | ~$2.15 | | 100 | ~$0.30 | ~$4.30 | | 500 | ~$1.50 | ~$21.50 |

Profile scraper: $0.003/profile. Post scraper: ~$0.04/lead (20 posts × $0.002).

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Error Handling

| Error | Fix | |-------|-----| | APIFY_API_TOKEN not set | Ask user to add it to .env | | Apify run fails or times out | Retry once. If still fails, skip that lead and note it. | | LinkedIn URL is invalid or profile not found | Skip the lead, report it to user | | 0 profiles returned | Check URL format — must be full LinkedIn URL with https:// | | Post scraper returns 0 posts | Person doesn't post publicly. Use profile data only for personalization. |